M-Index (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
All Classes All Packages

M

m - Variable in class elki.clustering.kmeans.FuzzyCMeans: Weight exponent
m - Variable in class elki.clustering.kmeans.FuzzyCMeans.Par: Weight exponent
m - Variable in class elki.clustering.kmeans.initialization.KMC2.Instance: Number of sampling attempts.
m - Variable in class elki.clustering.kmeans.initialization.KMC2: Number of sampling attempts.
m - Variable in class elki.clustering.kmeans.initialization.KMC2.Par: Number of sampling attempts.
m - Variable in class elki.index.laesa.LAESA.Factory: Number of reference points
m - Variable in class elki.index.laesa.LAESA.Factory.Par: Number of reference points
m - Variable in class elki.index.laesa.LAESA: Number of reference points
m - Variable in class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ApproximationLine: The incline.
m - Variable in class elki.math.geometry.SweepHullDelaunay2D.Triangle: Center double[]
m - Variable in class elki.math.linearalgebra.LUDecomposition: Row and column dimensions, and pivot sign.
m - Variable in class elki.math.linearalgebra.pca.AutotuningPCA.Cand: Candidate matrix
m - Variable in class elki.math.linearalgebra.QRDecomposition: Row and column dimensions.
m - Variable in class elki.math.linearalgebra.SingularValueDecomposition: Row and column dimensions.
m - Variable in class elki.math.statistics.dependence.HiCSDependence: Monte-Carlo iterations
m - Variable in class elki.math.statistics.dependence.HiCSDependence.Par: Monte-Carlo iterations
m - Variable in class elki.math.statistics.dependence.MCDEDependence: Monte-Carlo iterations.
m - Variable in class elki.math.statistics.dependence.MCDEDependence.Par: Holds the value of MCDEDependence.Par.M_ID.
m - Variable in class elki.math.statistics.LinearRegression
m - Variable in class elki.outlier.lof.INFLO: Pruning threshold m.
m - Variable in class elki.outlier.lof.INFLO.Par: M parameter
m - Variable in class elki.outlier.meta.HiCS: Monte-Carlo iterations.
m - Variable in class elki.outlier.subspace.AggarwalYuEvolutionary: Holds the value of AggarwalYuEvolutionary.Par.M_ID.
m - Variable in class elki.outlier.subspace.AggarwalYuEvolutionary.Par: Population size.
m_czech - Variable in class elki.math.linearalgebra.pca.PCAFilteredResult: The dissimilarity matrix.
m_hat - Variable in class elki.math.linearalgebra.pca.PCAFilteredResult: The similarity matrix.
m_i - Variable in class elki.clustering.subspace.PROCLUS: Multiplier for the initial number of medoids.
m_i - Variable in class elki.clustering.subspace.PROCLUS.Par: Multiplier for the initial number of medoids.
M_I_ID - Static variable in class elki.clustering.subspace.PROCLUS.Par: Parameter to specify the multiplier for the initial number of medoids, must be an integer greater than 0.
M_ID - Static variable in class elki.clustering.kmeans.FuzzyCMeans.Par: Parameter to set weight exponent
M_ID - Static variable in class elki.clustering.kmeans.initialization.KMC2.Par: Parameter m of the AFK-MC² method.
M_ID - Static variable in class elki.index.laesa.LAESA.Factory.Par: Number of reference points to choose.
M_ID - Static variable in class elki.math.statistics.dependence.HiCSDependence.Par: Parameter that specifies the number of iterations in the Monte-Carlo process of identifying high contrast subspaces.
M_ID - Static variable in class elki.math.statistics.dependence.MCDEDependence.Par: Parameter that specifies the number of iterations in the Monte-Carlo process of identifying high contrast subspaces.
M_ID - Static variable in class elki.outlier.lof.INFLO.Par: Parameter to specify if any object is a Core Object must be a double greater than 0.0
M_ID - Static variable in class elki.outlier.subspace.AggarwalYuEvolutionary.Par: Parameter to specify the number of solutions must be an integer greater than 1.
m1 - Variable in class elki.clustering.silhouette.FastMSC.Record: Nearest medoid
m2 - Variable in class elki.clustering.silhouette.FastMSC.Record: Second nearest medoid
m2 - Variable in class elki.math.MeanVariance: n times Variance
m3 - Variable in class elki.clustering.silhouette.FastMSC.Record: Third nearest medoid
m3 - Variable in class elki.math.StatisticalMoments: Third moment.
m4 - Variable in class elki.math.StatisticalMoments: Fourth moment.
MacQueenKMeans<V extends NumberVector> - Class in elki.clustering.kmeans: The original k-means algorithm, using MacQueen style incremental updates; making this effectively an "online" (streaming) algorithm.
MacQueenKMeans(NumberVectorDistance<? super V>, int, int, KMeansInitialization) - Constructor for class elki.clustering.kmeans.MacQueenKMeans: Constructor.
MacQueenKMeans.Instance - Class in elki.clustering.kmeans: Inner instance, storing state for a single data set.
MacQueenKMeans.Par<V extends NumberVector> - Class in elki.clustering.kmeans: Parameterization class.
MADDistributionEstimator<D extends Distribution> - Interface in elki.math.statistics.distribution.estimator: Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.
madests - Variable in class elki.math.statistics.distribution.estimator.meta.BestFitEstimator: Median average deviation from median estimators.
magic - Variable in class elki.persistent.OnDiskArray: Magic number used to identify files.
MAGIC - Static variable in class elki.datasource.bundle.BundleReader: Magic number, shared with BundleReader.
MAGIC - Static variable in class elki.datasource.bundle.BundleWriter: Random magic number.
magic_class - Variable in class elki.datasource.parser.ArffParser: Pattern to recognize class label columns.
magic_class - Variable in class elki.datasource.parser.ArffParser.Par: Pattern to recognize class label columns
MAGIC_CLASS_ID - Static variable in class elki.datasource.parser.ArffParser.Par: Pattern for recognizing class label attributes.
magic_eid - Variable in class elki.datasource.parser.ArffParser: Pattern to recognize external ids.
magic_eid - Variable in class elki.datasource.parser.ArffParser.Par: Pattern to recognize external ids
MAGIC_EID_ID - Static variable in class elki.datasource.parser.ArffParser.Par: Pattern for recognizing external ID attributes.
magnitude(int) - Static method in class elki.utilities.datastructures.BitsUtil: The magnitude is the position of the highest bit set
magnitude(long) - Static method in class elki.utilities.datastructures.BitsUtil: The magnitude is the position of the highest bit set
magnitude(long[]) - Static method in class elki.utilities.datastructures.BitsUtil: The magnitude is the position of the highest bit set
mahalanobisDistance(double[]) - Method in class elki.clustering.em.models.DiagonalGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(double[]) - Method in class elki.clustering.em.models.MultivariateGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(double[]) - Method in class elki.clustering.em.models.SphericalGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(double[]) - Method in class elki.clustering.em.models.TextbookSphericalGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(double[][], double[], double[]) - Static method in class elki.math.linearalgebra.VMath: Matrix multiplication, (a-c)^T * B * (a-c)
mahalanobisDistance(NumberVector) - Method in class elki.clustering.em.models.DiagonalGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(NumberVector) - Method in class elki.clustering.em.models.MultivariateGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(NumberVector) - Method in class elki.clustering.em.models.SphericalGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(NumberVector) - Method in class elki.clustering.em.models.TextbookMultivariateGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(NumberVector) - Method in class elki.clustering.em.models.TextbookSphericalGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
mahalanobisDistance(NumberVector) - Method in class elki.clustering.em.models.TwoPassMultivariateGaussianModel: Compute the Mahalanobis distance from the centroid for a given vector.
MahalanobisDistance - Class in elki.distance: Mahalanobis quadratic form distance for feature vectors.
MahalanobisDistance(double[][]) - Constructor for class elki.distance.MahalanobisDistance: Constructor.
main(String[]) - Static method in class elki.application.benchmark.KNNBenchmark: Runs the benchmark
main(String[]) - Static method in class elki.application.benchmark.PrioritySearchBenchmark: Runs the benchmark
main(String[]) - Static method in class elki.application.benchmark.RangeQueryBenchmark: Runs the benchmark
main(String[]) - Static method in class elki.application.cache.CacheDoubleDistanceInOnDiskMatrix: Main method, delegate to super class.
main(String[]) - Static method in class elki.application.cache.CacheDoubleDistanceKNNLists: Main method, delegate to super class.
main(String[]) - Static method in class elki.application.cache.CacheDoubleDistanceRangeQueries: Main method, delegate to super class.
main(String[]) - Static method in class elki.application.cache.CacheFloatDistanceInOnDiskMatrix: Main method, delegate to super class.
main(String[]) - Static method in class elki.application.cache.PrecomputeDistancesAsciiApplication: Main method, delegate to super class.
main(String[]) - Static method in class elki.application.ClassifierHoldoutEvaluationTask: Runs the classifier evaluation task accordingly to the specified parameters.
main(String[]) - Static method in class elki.application.ConvertToBundleApplication: Run command line application.
main(String[]) - Static method in class elki.application.ELKILauncher: Launch ELKI.
main(String[]) - Static method in class elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators: Main method
main(String[]) - Static method in class elki.application.experiments.ORLibBenchmark: Main method, delegate to super class.
main(String[]) - Static method in class elki.application.experiments.VisualizeGeodesicDistances: Main method for application.
main(String[]) - Static method in class elki.application.GeneratorXMLSpec: Main method to run this application.
main(String[]) - Static method in class elki.application.greedyensemble.ComputeKNNOutlierScores: Main method.
main(String[]) - Static method in class elki.application.greedyensemble.EvaluatePrecomputedOutlierScores: Main method.
main(String[]) - Static method in class elki.application.greedyensemble.GreedyEnsembleExperiment: Main method.
main(String[]) - Static method in class elki.application.greedyensemble.VisualizePairwiseGainMatrix: Main method.
main(String[]) - Static method in class elki.application.internal.CheckELKIServices: Main method.
main(String[]) - Static method in class elki.application.internal.CheckParameterizables
main(String[]) - Static method in class elki.application.KDDCLIApplication: Runs a KDD task accordingly to the specified parameters.
main(String[]) - Static method in class elki.gui.minigui.MiniGUI: Main method that just spawns the UI.
main(String[]) - Static method in class elki.gui.multistep.MultiStepGUI: Main method that just spawns the UI.
main(String[]) - Static method in class elki.KDDTask: Runs a KDD task accordingly to the specified parameters.
main(String[]) - Static method in class tutorial.javaapi.GeoIndexing
main(String[]) - Static method in class tutorial.javaapi.PassingDataToELKI: Main method
maincls - Variable in class elki.gui.minigui.MiniGUI: Application to configure / run.
make() - Method in class elki.algorithm.DependencyDerivator.Par
make() - Method in class elki.algorithm.KNNDistancesSampler.Par
make() - Method in class elki.algorithm.KNNJoin.Par
make() - Method in class elki.algorithm.statistics.AddSingleScale.Par
make() - Method in class elki.algorithm.statistics.DistanceQuantileSampler.Par
make() - Method in class elki.algorithm.statistics.HopkinsStatisticClusteringTendency.Par
make() - Method in class elki.application.AbstractApplication.Par
make() - Method in class elki.application.cache.CacheDoubleDistanceInOnDiskMatrix.Par
make() - Method in class elki.application.cache.CacheDoubleDistanceKNNLists.Par
make() - Method in class elki.application.cache.CacheDoubleDistanceRangeQueries.Par
make() - Method in class elki.application.cache.CacheFloatDistanceInOnDiskMatrix.Par
make() - Method in class elki.application.cache.PrecomputeDistancesAsciiApplication.Par
make() - Method in class elki.application.ClassifierHoldoutEvaluationTask.Par
make() - Method in class elki.application.ConvertToBundleApplication.Par
make() - Method in class elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Par
make() - Method in class elki.application.experiments.ORLibBenchmark.Par
make() - Method in class elki.application.experiments.VisualizeGeodesicDistances.Par
make() - Method in class elki.application.GeneratorXMLSpec.Par
make() - Method in class elki.application.greedyensemble.ComputeKNNOutlierScores.Par
make() - Method in class elki.application.greedyensemble.EvaluatePrecomputedOutlierScores.Par
make() - Method in class elki.application.greedyensemble.GreedyEnsembleExperiment.Par
make() - Method in class elki.application.greedyensemble.VisualizePairwiseGainMatrix.Par
make() - Method in class elki.application.KDDCLIApplication.Par
make() - Method in class elki.clustering.BetulaLeafPreClustering.Par
make() - Method in class elki.clustering.CFSFDP.Par
make() - Method in class elki.clustering.correlation.CASH.Par
make() - Method in class elki.clustering.correlation.COPAC.Par
make() - Method in class elki.clustering.correlation.ERiC.Par
make() - Method in class elki.clustering.correlation.FourC.Par
make() - Method in class elki.clustering.correlation.FourC.Settings.Par
make() - Method in class elki.clustering.correlation.HiCO.Par
make() - Method in class elki.clustering.correlation.LMCLUS.Par
make() - Method in class elki.clustering.correlation.ORCLUS.Par
make() - Method in class elki.clustering.dbscan.DBSCAN.Par
make() - Method in class elki.clustering.dbscan.GeneralizedDBSCAN.Par
make() - Method in class elki.clustering.dbscan.LSDBC.Par
make() - Method in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Par
make() - Method in class elki.clustering.dbscan.predicates.COPACNeighborPredicate.Par
make() - Method in class elki.clustering.dbscan.predicates.ERiCNeighborPredicate.Par
make() - Method in class elki.clustering.dbscan.predicates.FourCCorePredicate.Par
make() - Method in class elki.clustering.dbscan.predicates.FourCNeighborPredicate.Par
make() - Method in class elki.clustering.dbscan.predicates.MinPtsCorePredicate.Par
make() - Method in class elki.clustering.dbscan.predicates.PreDeConCorePredicate.Par
make() - Method in class elki.clustering.dbscan.predicates.PreDeConNeighborPredicate.Par
make() - Method in class elki.clustering.em.BetulaGMM.Par
make() - Method in class elki.clustering.em.BetulaGMMWeighted.Par
make() - Method in class elki.clustering.em.EM.Par
make() - Method in class elki.clustering.em.KDTreeEM.Par
make() - Method in class elki.clustering.em.models.BetulaDiagonalGaussianModelFactory.Par
make() - Method in class elki.clustering.em.models.BetulaMultivariateGaussianModelFactory.Par
make() - Method in class elki.clustering.em.models.BetulaSphericalGaussianModelFactory.Par
make() - Method in class elki.clustering.hierarchical.birch.AverageInterclusterDistance.Par
make() - Method in class elki.clustering.hierarchical.birch.AverageIntraclusterDistance.Par
make() - Method in class elki.clustering.hierarchical.birch.BIRCHKMeansPlusPlus.Par
make() - Method in class elki.clustering.hierarchical.birch.BIRCHLeafClustering.Par
make() - Method in class elki.clustering.hierarchical.birch.BIRCHLloydKMeans.Par
make() - Method in class elki.clustering.hierarchical.birch.CentroidEuclideanDistance.Par
make() - Method in class elki.clustering.hierarchical.birch.CentroidManhattanDistance.Par
make() - Method in class elki.clustering.hierarchical.birch.CFTree.Factory.Par
make() - Method in class elki.clustering.hierarchical.birch.DiameterCriterion.Par
make() - Method in class elki.clustering.hierarchical.birch.RadiusCriterion.Par
make() - Method in class elki.clustering.hierarchical.birch.VarianceIncreaseDistance.Par
make() - Method in class elki.clustering.hierarchical.CLINK.Par
make() - Method in class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Par
make() - Method in class elki.clustering.hierarchical.extraction.CutDendrogramByHeight.Par
make() - Method in class elki.clustering.hierarchical.extraction.CutDendrogramByNumberOfClusters.Par
make() - Method in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Par
make() - Method in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Par
make() - Method in class elki.clustering.hierarchical.linkage.CentroidLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.CompleteLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.FlexibleBetaLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.GroupAverageLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.MedianLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.MinimumVarianceLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.SingleLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.WardLinkage.Par
make() - Method in class elki.clustering.hierarchical.linkage.WeightedAverageLinkage.Par
make() - Method in class elki.clustering.hierarchical.OPTICSToHierarchical.Par
make() - Method in class elki.clustering.hierarchical.SLINK.Par
make() - Method in class elki.clustering.kcenter.GreedyKCenter.Par
make() - Method in class elki.clustering.kmeans.AbstractKMeans.Par
make() - Method in class elki.clustering.kmeans.AnnulusKMeans.Par
make() - Method in class elki.clustering.kmeans.BetulaLloydKMeans.Par
make() - Method in class elki.clustering.kmeans.CompareMeans.Par
make() - Method in class elki.clustering.kmeans.ElkanKMeans.Par
make() - Method in class elki.clustering.kmeans.ExponionKMeans.Par
make() - Method in class elki.clustering.kmeans.FuzzyCMeans.Par
make() - Method in class elki.clustering.kmeans.GMeans.Par
make() - Method in class elki.clustering.kmeans.HamerlyKMeans.Par
make() - Method in class elki.clustering.kmeans.HartiganWongKMeans.Parameterizer
make() - Method in class elki.clustering.kmeans.initialization.AFKMC2.Par
make() - Method in class elki.clustering.kmeans.initialization.betula.CFKPlusPlusLeaves.Par
make() - Method in class elki.clustering.kmeans.initialization.betula.CFKPlusPlusTree.Par
make() - Method in class elki.clustering.kmeans.initialization.betula.CFKPlusPlusTrunk.Par
make() - Method in class elki.clustering.kmeans.initialization.betula.CFRandomlyChosen.Par
make() - Method in class elki.clustering.kmeans.initialization.betula.CFWeightedRandomlyChosen.Par
make() - Method in class elki.clustering.kmeans.initialization.FarthestPoints.Par
make() - Method in class elki.clustering.kmeans.initialization.FarthestSumPoints.Par
make() - Method in class elki.clustering.kmeans.initialization.FirstK.Par
make() - Method in class elki.clustering.kmeans.initialization.KMC2.Par
make() - Method in class elki.clustering.kmeans.initialization.KMeansPlusPlus.Par
make() - Method in class elki.clustering.kmeans.initialization.Ostrovsky.Par
make() - Method in class elki.clustering.kmeans.initialization.Predefined.Par
make() - Method in class elki.clustering.kmeans.initialization.RandomlyChosen.Par
make() - Method in class elki.clustering.kmeans.initialization.RandomNormalGenerated.Par
make() - Method in class elki.clustering.kmeans.initialization.RandomUniformGenerated.Par
make() - Method in class elki.clustering.kmeans.initialization.SphericalAFKMC2.Par
make() - Method in class elki.clustering.kmeans.initialization.SphericalKMeansPlusPlus.Par
make() - Method in class elki.clustering.kmeans.KDTreeFilteringKMeans.Par
make() - Method in class elki.clustering.kmeans.KDTreePruningKMeans.Par
make() - Method in class elki.clustering.kmeans.KMeansMinusMinus.Par
make() - Method in class elki.clustering.kmeans.KMediansLloyd.Par
make() - Method in class elki.clustering.kmeans.LloydKMeans.Par
make() - Method in class elki.clustering.kmeans.MacQueenKMeans.Par
make() - Method in class elki.clustering.kmeans.ShallotKMeans.Par
make() - Method in class elki.clustering.kmeans.SimplifiedElkanKMeans.Par
make() - Method in class elki.clustering.kmeans.SingleAssignmentKMeans.Par
make() - Method in class elki.clustering.kmeans.SortMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalElkanKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalHamerlyKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalSimplifiedElkanKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.SphericalElkanKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.SphericalHamerlyKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.SphericalKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedElkanKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedHamerlyKMeans.Par
make() - Method in class elki.clustering.kmeans.spherical.SphericalSingleAssignmentKMeans.Par
make() - Method in class elki.clustering.kmeans.YinYangKMeans.Par
make() - Method in class elki.clustering.kmedoids.AlternatingKMedoids.Par
make() - Method in class elki.clustering.kmedoids.CLARA.Par
make() - Method in class elki.clustering.kmedoids.CLARANS.Par
make() - Method in class elki.clustering.kmedoids.EagerPAM.Par
make() - Method in class elki.clustering.kmedoids.FastCLARA.Par
make() - Method in class elki.clustering.kmedoids.FastCLARANS.Par
make() - Method in class elki.clustering.kmedoids.FasterCLARA.Par
make() - Method in class elki.clustering.kmedoids.FasterPAM.Par
make() - Method in class elki.clustering.kmedoids.FastPAM.Par
make() - Method in class elki.clustering.kmedoids.FastPAM1.Par
make() - Method in class elki.clustering.kmedoids.initialization.AlternateRefinement.Par
make() - Method in class elki.clustering.kmedoids.initialization.BUILD.Par
make() - Method in class elki.clustering.kmedoids.initialization.GreedyG.Par
make() - Method in class elki.clustering.kmedoids.initialization.KMedoidsKMedoidsInitialization.Par
make() - Method in class elki.clustering.kmedoids.initialization.LAB.Par
make() - Method in class elki.clustering.kmedoids.initialization.ParkJun.Par
make() - Method in class elki.clustering.kmedoids.PAM.Par
make() - Method in class elki.clustering.kmedoids.ReynoldsPAM.Par
make() - Method in class elki.clustering.kmedoids.SingleAssignmentKMedoids.Par
make() - Method in class elki.clustering.meta.ExternalClustering.Par
make() - Method in class elki.clustering.onedimensional.KNNKernelDensityMinimaClustering.Par
make() - Method in class elki.clustering.optics.DeLiClu.Par
make() - Method in class elki.clustering.optics.OPTICSHeap.Par
make() - Method in class elki.clustering.optics.OPTICSList.Par
make() - Method in class elki.clustering.optics.OPTICSXi.Par
make() - Method in class elki.clustering.silhouette.FasterMSC.Par
make() - Method in class elki.clustering.silhouette.FastMSC.Par
make() - Method in class elki.clustering.silhouette.PAMMEDSIL.Par
make() - Method in class elki.clustering.silhouette.PAMSIL.Par
make() - Method in class elki.clustering.subspace.CLIQUE.Par
make() - Method in class elki.clustering.subspace.DiSH.Par
make() - Method in class elki.clustering.subspace.DOC.Par
make() - Method in class elki.clustering.subspace.FastDOC.Par
make() - Method in class elki.clustering.subspace.HiSC.Par
make() - Method in class elki.clustering.subspace.P3C.Par
make() - Method in class elki.clustering.subspace.PreDeCon.Par
make() - Method in class elki.clustering.subspace.PreDeCon.Settings.Par
make() - Method in class elki.clustering.subspace.PROCLUS.Par
make() - Method in class elki.clustering.subspace.SUBCLU.Par
make() - Method in class elki.clustering.trivial.ByLabelClustering.Par
make() - Method in class elki.clustering.trivial.ByModelClustering.Par
make() - Method in class elki.clustering.uncertain.CenterOfMassMetaClustering.Par
make() - Method in class elki.clustering.uncertain.CKMeans.Par
make() - Method in class elki.clustering.uncertain.FDBSCAN.Par
make() - Method in class elki.clustering.uncertain.FDBSCANNeighborPredicate.Par
make() - Method in class elki.clustering.uncertain.RepresentativeUncertainClustering.Par
make() - Method in class elki.clustering.uncertain.UKMeans.Par
make() - Method in class elki.data.BitVector.Factory.Par
make() - Method in class elki.data.ByteVector.Factory.Par
make() - Method in class elki.data.DoubleVector.Factory.Par
make() - Method in class elki.data.FloatVector.Factory.Par
make() - Method in class elki.data.IntegerVector.Factory.Par
make() - Method in class elki.data.OneDimensionalDoubleVector.Factory.Par
make() - Method in class elki.data.projection.FeatureSelection.Par
make() - Method in class elki.data.projection.NumericalFeatureSelection.Par
make() - Method in class elki.data.projection.random.AchlioptasRandomProjectionFamily.Par
make() - Method in class elki.data.projection.random.CauchyRandomProjectionFamily.Par
make() - Method in class elki.data.projection.random.GaussianRandomProjectionFamily.Par
make() - Method in class elki.data.projection.random.RandomSubsetProjectionFamily.Par
make() - Method in class elki.data.projection.random.SimplifiedRandomHyperplaneProjectionFamily.Par
make() - Method in class elki.data.projection.RandomProjection.Par
make() - Method in class elki.data.ShortVector.Factory.Par
make() - Method in class elki.data.SparseByteVector.Factory.Par
make() - Method in class elki.data.SparseDoubleVector.Factory.Par
make() - Method in class elki.data.SparseFloatVector.Factory.Par
make() - Method in class elki.data.SparseIntegerVector.Factory.Par
make() - Method in class elki.data.SparseShortVector.Factory.Par
make() - Method in class elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier.Par
make() - Method in class elki.data.uncertain.uncertainifier.UniformUncertainifier.Par
make() - Method in class elki.data.uncertain.uncertainifier.UnweightedDiscreteUncertainifier.Par
make() - Method in class elki.data.uncertain.uncertainifier.WeightedDiscreteUncertainifier.Par
make() - Method in class elki.database.AbstractDatabase.Par
make() - Method in class elki.database.HashmapDatabase.Par
make() - Method in class elki.database.query.DisableQueryOptimizer.Par
make() - Method in class elki.database.StaticArrayDatabase.Par
make() - Method in class elki.datasource.BundleDatabaseConnection.Par
make() - Method in class elki.datasource.ConcatenateFilesDatabaseConnection.Par
make() - Method in class elki.datasource.DBIDRangeDatabaseConnection.Par
make() - Method in class elki.datasource.ExternalIDJoinDatabaseConnection.Par
make() - Method in class elki.datasource.FileBasedDatabaseConnection.Par
make() - Method in class elki.datasource.filter.cleaning.DropNaNFilter.Par
make() - Method in class elki.datasource.filter.cleaning.NoMissingValuesFilter.Par
make() - Method in class elki.datasource.filter.cleaning.ReplaceNaNWithRandomFilter.Par
make() - Method in class elki.datasource.filter.FixedDBIDsFilter.Par
make() - Method in class elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Par
make() - Method in class elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization.Par
make() - Method in class elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization.Par
make() - Method in class elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization.Par
make() - Method in class elki.datasource.filter.normalization.instancewise.HellingerHistogramNormalization.Par
make() - Method in class elki.datasource.filter.normalization.instancewise.InstanceLogRankNormalization.Par
make() - Method in class elki.datasource.filter.normalization.instancewise.InstanceMeanVarianceNormalization.Par
make() - Method in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization.Par
make() - Method in class elki.datasource.filter.normalization.instancewise.InstanceRankNormalization.Par
make() - Method in class elki.datasource.filter.normalization.instancewise.LengthNormalization.Par
make() - Method in class elki.datasource.filter.normalization.instancewise.Log1PlusNormalization.Par
make() - Method in class elki.datasource.filter.selection.ByLabelFilter.Par
make() - Method in class elki.datasource.filter.selection.FirstNStreamFilter.Par
make() - Method in class elki.datasource.filter.selection.RandomSamplingStreamFilter.Par
make() - Method in class elki.datasource.filter.selection.ShuffleObjectsFilter.Par
make() - Method in class elki.datasource.filter.transform.FastMultidimensionalScalingTransform.Par
make() - Method in class elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform.Par
make() - Method in class elki.datasource.filter.transform.HistogramJitterFilter.Par
make() - Method in class elki.datasource.filter.transform.LinearDiscriminantAnalysisFilter.Par
make() - Method in class elki.datasource.filter.transform.NumberVectorFeatureSelectionFilter.Par
make() - Method in class elki.datasource.filter.transform.NumberVectorRandomFeatureSelectionFilter.Par
make() - Method in class elki.datasource.filter.transform.PerturbationFilter.Par
make() - Method in class elki.datasource.filter.typeconversions.ClassLabelFilter.Par
make() - Method in class elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter.Par
make() - Method in class elki.datasource.filter.typeconversions.ExternalIDFilter.Par
make() - Method in class elki.datasource.filter.typeconversions.SplitNumberVectorFilter.Par
make() - Method in class elki.datasource.filter.typeconversions.UncertainifyFilter.Par
make() - Method in class elki.datasource.filter.typeconversions.UncertainSplitFilter.Par
make() - Method in class elki.datasource.filter.typeconversions.WeightedUncertainSplitFilter.Par
make() - Method in class elki.datasource.GeneratorXMLDatabaseConnection.Par
make() - Method in class elki.datasource.InputStreamDatabaseConnection.Par
make() - Method in class elki.datasource.LabelJoinDatabaseConnection.Par
make() - Method in class elki.datasource.parser.AbstractStreamingParser.Par
make() - Method in class elki.datasource.parser.ArffParser.Par
make() - Method in class elki.datasource.parser.BitVectorLabelParser.Par
make() - Method in class elki.datasource.parser.CategorialDataAsNumberVectorParser.Par
make() - Method in class elki.datasource.parser.ClusteringVectorParser.Par
make() - Method in class elki.datasource.parser.CSVReaderFormat.Par
make() - Method in class elki.datasource.parser.LibSVMFormatParser.Par
make() - Method in class elki.datasource.parser.NumberVectorLabelParser.Par
make() - Method in class elki.datasource.parser.SimplePolygonParser.Par
make() - Method in class elki.datasource.parser.SimpleTransactionParser.Par
make() - Method in class elki.datasource.parser.SparseNumberVectorLabelParser.Par
make() - Method in class elki.datasource.parser.StringParser.Par
make() - Method in class elki.datasource.parser.TermFrequencyParser.Par
make() - Method in class elki.datasource.PresortedBlindJoinDatabaseConnection.Par
make() - Method in class elki.datasource.RandomDoubleVectorDatabaseConnection.Par
make() - Method in class elki.distance.adapter.ArccosSimilarityAdapter.Par
make() - Method in class elki.distance.adapter.LinearSimilarityAdapter.Par
make() - Method in class elki.distance.adapter.LnSimilarityAdapter.Par
make() - Method in class elki.distance.ArcCosineDistance.Par
make() - Method in class elki.distance.ArcCosineUnitlengthDistance.Par
make() - Method in class elki.distance.BrayCurtisDistance.Par
make() - Method in class elki.distance.CanberraDistance.Par
make() - Method in class elki.distance.ClarkDistance.Par
make() - Method in class elki.distance.colorhistogram.HistogramIntersectionDistance.Par
make() - Method in class elki.distance.colorhistogram.HSBHistogramQuadraticDistance.Par
make() - Method in class elki.distance.colorhistogram.RGBHistogramQuadraticDistance.Par
make() - Method in class elki.distance.correlation.AbsolutePearsonCorrelationDistance.Par
make() - Method in class elki.distance.correlation.AbsoluteUncenteredCorrelationDistance.Par
make() - Method in class elki.distance.correlation.PearsonCorrelationDistance.Par
make() - Method in class elki.distance.correlation.SquaredPearsonCorrelationDistance.Par
make() - Method in class elki.distance.correlation.SquaredUncenteredCorrelationDistance.Par
make() - Method in class elki.distance.correlation.UncenteredCorrelationDistance.Par
make() - Method in class elki.distance.correlation.WeightedPearsonCorrelationDistance.Par
make() - Method in class elki.distance.correlation.WeightedSquaredPearsonCorrelationDistance.Par
make() - Method in class elki.distance.CosineDistance.Par
make() - Method in class elki.distance.CosineUnitlengthDistance.Par
make() - Method in class elki.distance.external.AsciiDistanceParser.Par
make() - Method in class elki.distance.external.DiskCacheBasedDoubleDistance.Par
make() - Method in class elki.distance.external.DiskCacheBasedFloatDistance.Par
make() - Method in class elki.distance.external.FileBasedSparseDoubleDistance.Par
make() - Method in class elki.distance.external.FileBasedSparseFloatDistance.Par
make() - Method in class elki.distance.geo.DimensionSelectingLatLngDistance.Par
make() - Method in class elki.distance.geo.LatLngDistance.Par
make() - Method in class elki.distance.geo.LngLatDistance.Par
make() - Method in class elki.distance.histogram.HistogramMatchDistance.Par
make() - Method in class elki.distance.histogram.KolmogorovSmirnovDistance.Par
make() - Method in class elki.distance.minkowski.EuclideanDistance.Par
make() - Method in class elki.distance.minkowski.LPIntegerNormDistance.Par
make() - Method in class elki.distance.minkowski.LPNormDistance.Par
make() - Method in class elki.distance.minkowski.ManhattanDistance.Par
make() - Method in class elki.distance.minkowski.MaximumDistance.Par
make() - Method in class elki.distance.minkowski.MinimumDistance.Par
make() - Method in class elki.distance.minkowski.SparseEuclideanDistance.Par
make() - Method in class elki.distance.minkowski.SparseLPNormDistance.Par
make() - Method in class elki.distance.minkowski.SparseManhattanDistance.Par
make() - Method in class elki.distance.minkowski.SparseMaximumDistance.Par
make() - Method in class elki.distance.minkowski.SparseSquaredEuclideanDistance.Par
make() - Method in class elki.distance.minkowski.SquaredEuclideanDistance.Par
make() - Method in class elki.distance.minkowski.WeightedEuclideanDistance.Par
make() - Method in class elki.distance.minkowski.WeightedLPNormDistance.Par
make() - Method in class elki.distance.minkowski.WeightedManhattanDistance.Par
make() - Method in class elki.distance.minkowski.WeightedMaximumDistance.Par
make() - Method in class elki.distance.minkowski.WeightedSquaredEuclideanDistance.Par
make() - Method in class elki.distance.probabilistic.ChiDistance.Par
make() - Method in class elki.distance.probabilistic.ChiSquaredDistance.Par
make() - Method in class elki.distance.probabilistic.FisherRaoDistance.Par
make() - Method in class elki.distance.probabilistic.HellingerDistance.Par
make() - Method in class elki.distance.probabilistic.JeffreyDivergenceDistance.Par
make() - Method in class elki.distance.probabilistic.JensenShannonDivergenceDistance.Par
make() - Method in class elki.distance.probabilistic.KullbackLeiblerDivergenceAsymmetricDistance.Par
make() - Method in class elki.distance.probabilistic.KullbackLeiblerDivergenceReverseAsymmetricDistance.Par
make() - Method in class elki.distance.probabilistic.SqrtJensenShannonDivergenceDistance.Par
make() - Method in class elki.distance.probabilistic.TriangularDiscriminationDistance.Par
make() - Method in class elki.distance.probabilistic.TriangularDistance.Par
make() - Method in class elki.distance.RandomStableDistance.Par
make() - Method in class elki.distance.set.HammingDistance.Par
make() - Method in class elki.distance.SharedNearestNeighborJaccardDistance.Par
make() - Method in class elki.distance.SqrtCosineDistance.Par
make() - Method in class elki.distance.SqrtCosineUnitlengthDistance.Par
make() - Method in class elki.distance.strings.LevenshteinDistance.Par
make() - Method in class elki.distance.strings.NormalizedLevenshteinDistance.Par
make() - Method in class elki.distance.subspace.OnedimensionalDistance.Par
make() - Method in class elki.distance.subspace.SubspaceEuclideanDistance.Par
make() - Method in class elki.distance.subspace.SubspaceLPNormDistance.Par
make() - Method in class elki.distance.subspace.SubspaceManhattanDistance.Par
make() - Method in class elki.distance.subspace.SubspaceMaximumDistance.Par
make() - Method in class elki.distance.timeseries.DTWDistance.Par
make() - Method in class elki.distance.timeseries.EDRDistance.Par
make() - Method in class elki.distance.timeseries.ERPDistance.Par
make() - Method in class elki.distance.timeseries.LCSSDistance.Par
make() - Method in class elki.distance.WeightedCanberraDistance.Par
make() - Method in class elki.evaluation.AutomaticEvaluation.Par
make() - Method in class elki.evaluation.classification.holdout.DisjointCrossValidation.Par
make() - Method in class elki.evaluation.classification.holdout.RandomizedCrossValidation.Par
make() - Method in class elki.evaluation.classification.holdout.StratifiedCrossValidation.Par
make() - Method in class elki.evaluation.clustering.EvaluateClustering.Par
make() - Method in class elki.evaluation.clustering.extractor.CutDendrogramByHeightExtractor.Par
make() - Method in class elki.evaluation.clustering.extractor.CutDendrogramByNumberOfClustersExtractor.Par
make() - Method in class elki.evaluation.clustering.extractor.HDBSCANHierarchyExtractionEvaluator.Par
make() - Method in class elki.evaluation.clustering.extractor.SimplifiedHierarchyExtractionEvaluator.Par
make() - Method in class elki.evaluation.clustering.internal.CIndex.Par
make() - Method in class elki.evaluation.clustering.internal.ClusterRadius.Par
make() - Method in class elki.evaluation.clustering.internal.ConcordantPairsGammaTau.Par
make() - Method in class elki.evaluation.clustering.internal.DaviesBouldinIndex.Par
make() - Method in class elki.evaluation.clustering.internal.DBCV.Par
make() - Method in class elki.evaluation.clustering.internal.PBMIndex.Par
make() - Method in class elki.evaluation.clustering.internal.Silhouette.Par
make() - Method in class elki.evaluation.clustering.internal.SimplifiedSilhouette.Par
make() - Method in class elki.evaluation.clustering.internal.SquaredErrors.Par
make() - Method in class elki.evaluation.clustering.internal.VarianceRatioCriterion.Par
make() - Method in class elki.evaluation.NoAutomaticEvaluation.Par
make() - Method in class elki.evaluation.outlier.ComputeOutlierHistogram.Par
make() - Method in class elki.evaluation.outlier.JudgeOutlierScores.Par
make() - Method in class elki.evaluation.outlier.OutlierPrecisionAtKCurve.Par
make() - Method in class elki.evaluation.outlier.OutlierPrecisionRecallCurve.Par
make() - Method in class elki.evaluation.outlier.OutlierPrecisionRecallGainCurve.Par
make() - Method in class elki.evaluation.outlier.OutlierRankingEvaluation.Par
make() - Method in class elki.evaluation.outlier.OutlierROCCurve.Par
make() - Method in class elki.evaluation.outlier.OutlierSmROCCurve.Par
make() - Method in class elki.evaluation.outlier.OutlierThresholdClustering.Par
make() - Method in class elki.evaluation.scores.AUPRCEvaluation.Par
make() - Method in class elki.evaluation.scores.AveragePrecisionEvaluation.Par
make() - Method in class elki.evaluation.scores.DCGEvaluation.Par
make() - Method in class elki.evaluation.scores.MaximumF1Evaluation.Par
make() - Method in class elki.evaluation.scores.NDCGEvaluation.Par
make() - Method in class elki.evaluation.scores.PrecisionAtKEvaluation.Par
make() - Method in class elki.evaluation.scores.PRGCEvaluation.Par
make() - Method in class elki.evaluation.scores.ROCEvaluation.Par
make() - Method in class elki.evaluation.similaritymatrix.ComputeSimilarityMatrixImage.Par
make() - Method in class elki.index.laesa.LAESA.Factory.Par
make() - Method in class elki.index.lsh.hashfamilies.CosineHashFunctionFamily.Par
make() - Method in class elki.index.lsh.hashfamilies.EuclideanHashFunctionFamily.Par
make() - Method in class elki.index.lsh.hashfamilies.ManhattanHashFunctionFamily.Par
make() - Method in class elki.index.lsh.InMemoryLSHIndex.Par
make() - Method in class elki.index.PagedIndexFactory.Par
make() - Method in class elki.index.preprocessed.fastoptics.RandomProjectedNeighborsAndDensities.Par
make() - Method in class elki.index.preprocessed.knn.CachedDoubleDistanceKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.knn.MaterializeKNNAndRKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.knn.MaterializeKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.knn.MetricalIndexApproximationMaterializeKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.knn.NaiveProjectedKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.knn.PartitionApproximationMaterializeKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.knn.SpacefillingKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.knn.SpatialApproximationMaterializeKNNPreprocessor.Factory.Par
make() - Method in class elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor.Factory.Par
make() - Method in class elki.index.tree.betula.CFTree.Factory.Par
make() - Method in class elki.index.tree.betula.distance.AverageInterclusterDistance.Par
make() - Method in class elki.index.tree.betula.distance.AverageIntraclusterDistance.Par
make() - Method in class elki.index.tree.betula.distance.BIRCHAverageInterclusterDistance.Par
make() - Method in class elki.index.tree.betula.distance.BIRCHAverageIntraclusterDistance.Par
make() - Method in class elki.index.tree.betula.distance.BIRCHRadiusDistance.Par
make() - Method in class elki.index.tree.betula.distance.BIRCHVarianceIncreaseDistance.Par
make() - Method in class elki.index.tree.betula.distance.CentroidEuclideanDistance.Par
make() - Method in class elki.index.tree.betula.distance.CentroidManhattanDistance.Par
make() - Method in class elki.index.tree.betula.distance.RadiusDistance.Par
make() - Method in class elki.index.tree.betula.distance.VarianceIncreaseDistance.Par
make() - Method in class elki.index.tree.betula.features.BIRCHCF.Factory.Par
make() - Method in class elki.index.tree.betula.features.VIIFeature.Factory.Par
make() - Method in class elki.index.tree.betula.features.VVIFeature.Factory.Par
make() - Method in class elki.index.tree.betula.features.VVVFeature.Factory.Par
make() - Method in class elki.index.tree.metrical.covertree.CoverTree.Factory.Par
make() - Method in class elki.index.tree.metrical.covertree.SimplifiedCoverTree.Factory.Par
make() - Method in class elki.index.tree.metrical.mtreevariants.AbstractMTreeFactory.Par
make() - Method in class elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTreeUnifiedFactory.Par
make() - Method in class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeFactory.Par
make() - Method in class elki.index.tree.metrical.vptree.GNAT.Factory.Par
make() - Method in class elki.index.tree.metrical.vptree.VPTree.Factory.Par
make() - Method in class elki.index.tree.spatial.kd.MemoryKDTree.Factory.Par
make() - Method in class elki.index.tree.spatial.kd.MinimalisticMemoryKDTree.Factory.Par
make() - Method in class elki.index.tree.spatial.kd.SmallMemoryKDTree.Factory.Par
make() - Method in class elki.index.tree.spatial.kd.split.BoundedMidpointSplit.Par
make() - Method in class elki.index.tree.spatial.kd.split.LeastOneDimSSQSplit.Par
make() - Method in class elki.index.tree.spatial.kd.split.LeastSSQSplit.Par
make() - Method in class elki.index.tree.spatial.kd.split.MeanVarianceSplit.Par
make() - Method in class elki.index.tree.spatial.kd.split.MedianSplit.Par
make() - Method in class elki.index.tree.spatial.kd.split.MedianVarianceSplit.Par
make() - Method in class elki.index.tree.spatial.kd.split.MidpointSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeFactory.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.flat.FlatRStarTreeFactory.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTreeFactory.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.bulk.AdaptiveSortTileRecursiveBulkSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.bulk.FileOrderBulkSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.bulk.MaxExtensionBulkSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.bulk.MaxExtensionSortTileRecursiveBulkSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.bulk.OneDimSortBulkSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.bulk.SortTileRecursiveBulkSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.bulk.SpatialSortBulkSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.insert.ApproximativeLeastOverlapInsertionStrategy.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.insert.CombinedInsertionStrategy.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.insert.LeastEnlargementInsertionStrategy.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.insert.LeastEnlargementWithAreaInsertionStrategy.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.insert.LeastOverlapInsertionStrategy.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.overflow.LimitedReinsertOverflowTreatment.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.overflow.SplitOnlyOverflowTreatment.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.reinsert.CloseReinsert.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.reinsert.FarReinsert.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.split.AngTanLinearSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.split.GreeneSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.split.RTreeLinearSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.split.RTreeQuadraticSplit.Par
make() - Method in class elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Par
make() - Method in class elki.index.vafile.PartialVAFile.Factory.Par
make() - Method in class elki.index.vafile.VAFile.Factory.Par
make() - Method in class elki.itemsetmining.APRIORI.Par
make() - Method in class elki.itemsetmining.associationrules.AssociationRuleGeneration.Par
make() - Method in class elki.itemsetmining.Eclat.Par
make() - Method in class elki.itemsetmining.FPGrowth.Par
make() - Method in class elki.KDDTask.Par
make() - Method in class elki.math.geodesy.Clarke1858SpheroidEarthModel.Par
make() - Method in class elki.math.geodesy.Clarke1880SpheroidEarthModel.Par
make() - Method in class elki.math.geodesy.GRS67SpheroidEarthModel.Par
make() - Method in class elki.math.geodesy.GRS80SpheroidEarthModel.Par
make() - Method in class elki.math.geodesy.SphericalCosineEarthModel.Par
make() - Method in class elki.math.geodesy.SphericalHaversineEarthModel.Par
make() - Method in class elki.math.geodesy.SphericalVincentyEarthModel.Par
make() - Method in class elki.math.geodesy.WGS72SpheroidEarthModel.Par
make() - Method in class elki.math.geodesy.WGS84SpheroidEarthModel.Par
make() - Method in class elki.math.linearalgebra.pca.AutotuningPCA.Par
make() - Method in class elki.math.linearalgebra.pca.filter.DropEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.filter.FirstNEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.filter.LimitEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.filter.PercentageEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.filter.ProgressiveEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.filter.RelativeEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.filter.SignificantEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.filter.WeakEigenPairFilter.Par
make() - Method in class elki.math.linearalgebra.pca.PCARunner.Par
make() - Method in class elki.math.linearalgebra.pca.RANSACCovarianceMatrixBuilder.Par
make() - Method in class elki.math.linearalgebra.pca.WeightedCovarianceMatrixBuilder.Par
make() - Method in class elki.math.spacefillingcurves.BinarySplitSpatialSorter.Par
make() - Method in class elki.math.spacefillingcurves.HilbertSpatialSorter.Par
make() - Method in class elki.math.spacefillingcurves.PeanoSpatialSorter.Par
make() - Method in class elki.math.spacefillingcurves.ZCurveSpatialSorter.Par
make() - Method in class elki.math.statistics.dependence.DCor.Par
make() - Method in class elki.math.statistics.dependence.HiCSDependence.Par
make() - Method in class elki.math.statistics.dependence.HoeffdingsD.Par
make() - Method in class elki.math.statistics.dependence.HoughSpaceMeasure.Par
make() - Method in class elki.math.statistics.dependence.JensenShannonEquiwidthDependence.Par
make() - Method in class elki.math.statistics.dependence.MaximumConditionalEntropy.Par
make() - Method in class elki.math.statistics.dependence.mcde.MWPTest.Par
make() - Method in class elki.math.statistics.dependence.MCDEDependence.Par
make() - Method in class elki.math.statistics.dependence.MutualInformationEquiwidthDependence.Par
make() - Method in class elki.math.statistics.dependence.PearsonCorrelationDependence.Par
make() - Method in class elki.math.statistics.dependence.SlopeDependence.Par
make() - Method in class elki.math.statistics.dependence.SlopeInversionDependence.Par
make() - Method in class elki.math.statistics.dependence.SpearmanCorrelationDependence.Par
make() - Method in class elki.math.statistics.dependence.SURFINGDependence.Par
make() - Method in class elki.math.statistics.distribution.BetaDistribution.Par
make() - Method in class elki.math.statistics.distribution.CauchyDistribution.Par
make() - Method in class elki.math.statistics.distribution.ChiDistribution.Par
make() - Method in class elki.math.statistics.distribution.ChiSquaredDistribution.Par
make() - Method in class elki.math.statistics.distribution.ConstantDistribution.Par
make() - Method in class elki.math.statistics.distribution.estimator.CauchyMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.EMGOlivierNorbergEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.ExpGammaExpMOMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.ExponentialLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.ExponentialMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.ExponentialMedianEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.ExponentialMOMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GammaChoiWetteEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GammaLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GammaMOMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GeneralizedLogisticAlternateLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GeneralizedParetoLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GumbelLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.GumbelMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.InverseGaussianMLEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.InverseGaussianMOMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LaplaceLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LaplaceMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LaplaceMLEEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogGammaLogMOMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogisticLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogisticMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogLogisticMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogNormalBilkovaLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogNormalLevenbergMarquardtKDEEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogNormalLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogNormalLogMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.LogNormalLogMOMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.meta.BestFitEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.NormalLevenbergMarquardtKDEEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.NormalLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.NormalMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.NormalMOMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.RayleighLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.RayleighMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.RayleighMLEEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.SkewGNormalLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.UniformEnhancedMinMaxEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.UniformLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.UniformMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.UniformMinMaxEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.WeibullLMMEstimator.Par
make() - Method in class elki.math.statistics.distribution.estimator.WeibullLogMADEstimator.Par
make() - Method in class elki.math.statistics.distribution.ExpGammaDistribution.Par
make() - Method in class elki.math.statistics.distribution.ExponentialDistribution.Par
make() - Method in class elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution.Par
make() - Method in class elki.math.statistics.distribution.GammaDistribution.Par
make() - Method in class elki.math.statistics.distribution.GeneralizedExtremeValueDistribution.Par
make() - Method in class elki.math.statistics.distribution.GeneralizedLogisticAlternateDistribution.Par
make() - Method in class elki.math.statistics.distribution.GeneralizedLogisticDistribution.Par
make() - Method in class elki.math.statistics.distribution.GeneralizedParetoDistribution.Par
make() - Method in class elki.math.statistics.distribution.GumbelDistribution.Par
make() - Method in class elki.math.statistics.distribution.HaltonUniformDistribution.Par
make() - Method in class elki.math.statistics.distribution.InverseGaussianDistribution.Par
make() - Method in class elki.math.statistics.distribution.KappaDistribution.Par
make() - Method in class elki.math.statistics.distribution.LaplaceDistribution.Par
make() - Method in class elki.math.statistics.distribution.LogGammaDistribution.Par
make() - Method in class elki.math.statistics.distribution.LogisticDistribution.Par
make() - Method in class elki.math.statistics.distribution.LogLogisticDistribution.Par
make() - Method in class elki.math.statistics.distribution.LogNormalDistribution.Par
make() - Method in class elki.math.statistics.distribution.NormalDistribution.Par
make() - Method in class elki.math.statistics.distribution.PoissonDistribution.Par
make() - Method in class elki.math.statistics.distribution.RayleighDistribution.Par
make() - Method in class elki.math.statistics.distribution.SkewGeneralizedNormalDistribution.Par
make() - Method in class elki.math.statistics.distribution.StudentsTDistribution.Par
make() - Method in class elki.math.statistics.distribution.UniformDistribution.Par
make() - Method in class elki.math.statistics.distribution.WeibullDistribution.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.ABIDEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.AggregatedHillEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.ALIDEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.GEDEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.HillEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.LMomentsEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.LPCAEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.MOMEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.PWM2Estimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.PWMEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.RABIDEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.RVEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.TightLIDEstimator.Par
make() - Method in class elki.math.statistics.intrinsicdimensionality.ZipfEstimator.Par
make() - Method in class elki.math.statistics.kernelfunctions.BiweightKernelDensityFunction.Par
make() - Method in class elki.math.statistics.kernelfunctions.CosineKernelDensityFunction.Par
make() - Method in class elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction.Par
make() - Method in class elki.math.statistics.kernelfunctions.GaussianKernelDensityFunction.Par
make() - Method in class elki.math.statistics.kernelfunctions.TriangularKernelDensityFunction.Par
make() - Method in class elki.math.statistics.kernelfunctions.TricubeKernelDensityFunction.Par
make() - Method in class elki.math.statistics.kernelfunctions.TriweightKernelDensityFunction.Par
make() - Method in class elki.math.statistics.kernelfunctions.UniformKernelDensityFunction.Par
make() - Method in class elki.math.statistics.tests.KolmogorovSmirnovTest.Par
make() - Method in class elki.math.statistics.tests.WelchTTest.Par
make() - Method in class elki.outlier.anglebased.ABOD.Par
make() - Method in class elki.outlier.anglebased.FastABOD.Par
make() - Method in class elki.outlier.anglebased.LBABOD.Par
make() - Method in class elki.outlier.clustering.DBSCANOutlierDetection.Par
make() - Method in class elki.outlier.clustering.EMOutlier.Par
make() - Method in class elki.outlier.clustering.GLOSH.Par
make() - Method in class elki.outlier.clustering.KMeansMinusMinusOutlierDetection.Par
make() - Method in class elki.outlier.clustering.NoiseAsOutliers.Par
make() - Method in class elki.outlier.COP.Par
make() - Method in class elki.outlier.density.IsolationForest.Par
make() - Method in class elki.outlier.distance.DBOutlierDetection.Par
make() - Method in class elki.outlier.distance.DBOutlierScore.Par
make() - Method in class elki.outlier.distance.KNNDD.Par
make() - Method in class elki.outlier.distance.KNNOutlier.Par
make() - Method in class elki.outlier.distance.KNNWeightOutlier.Par
make() - Method in class elki.outlier.distance.LocalIsolationCoefficient.Par
make() - Method in class elki.outlier.distance.ReferenceBasedOutlierDetection.Par
make() - Method in class elki.outlier.GaussianModel.Par
make() - Method in class elki.outlier.GaussianUniformMixture.Par
make() - Method in class elki.outlier.intrinsic.IDOS.Par
make() - Method in class elki.outlier.intrinsic.LID.Par
make() - Method in class elki.outlier.lof.ALOCI.Par
make() - Method in class elki.outlier.lof.FlexibleLOF.Par
make() - Method in class elki.outlier.lof.INFLO.Par
make() - Method in class elki.outlier.lof.LDOF.Par
make() - Method in class elki.outlier.lof.OnlineLOF.Par
make() - Method in class elki.outlier.meta.ExternalDoubleOutlierScore.Par
make() - Method in class elki.outlier.meta.FeatureBagging.Par
make() - Method in class elki.outlier.meta.RescaleMetaOutlierAlgorithm.Par
make() - Method in class elki.outlier.meta.SimpleOutlierEnsemble.Par
make() - Method in class elki.outlier.OPTICSOF.Par
make() - Method in class elki.outlier.SimpleCOP.Par
make() - Method in class elki.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory.Par
make() - Method in class elki.outlier.spatial.neighborhood.ExternalNeighborhood.Factory.Par
make() - Method in class elki.outlier.spatial.neighborhood.weighted.LinearWeightedExtendedNeighborhood.Factory.Par
make() - Method in class elki.outlier.subspace.AggarwalYuEvolutionary.Par
make() - Method in class elki.outlier.subspace.AggarwalYuNaive.Par
make() - Method in class elki.outlier.subspace.OutRankS1.Par
make() - Method in class elki.outlier.subspace.OUTRES.Par
make() - Method in class elki.outlier.subspace.SOD.Par
make() - Method in class elki.outlier.trivial.ByLabelOutlier.Par
make() - Method in class elki.outlier.trivial.TrivialGeneratedOutlier.Par
make() - Method in class elki.persistent.LRUCachePageFileFactory.Par
make() - Method in class elki.persistent.MemoryPageFileFactory.Par
make() - Method in class elki.projection.GaussianAffinityMatrixBuilder.Par
make() - Method in class elki.projection.IntrinsicNearestNeighborAffinityMatrixBuilder.Par
make() - Method in class elki.projection.NearestNeighborAffinityMatrixBuilder.Par
make() - Method in class elki.projection.PerplexityAffinityMatrixBuilder.Par
make() - Method in class elki.result.AutomaticVisualization.Par
make() - Method in class elki.result.ClusteringVectorDumper.Par
make() - Method in class elki.result.ExportVisualizations.Par
make() - Method in class elki.result.KMLOutputHandler.Par
make() - Method in class elki.result.ResultWriter.Par
make() - Method in class elki.similarity.cluster.ClusteringAdjustedRandIndexSimilarity.Par
make() - Method in class elki.similarity.cluster.ClusteringBCubedF1Similarity.Par
make() - Method in class elki.similarity.cluster.ClusteringFowlkesMallowsSimilarity.Par
make() - Method in class elki.similarity.cluster.ClusteringRandIndexSimilarity.Par
make() - Method in class elki.similarity.cluster.ClusterIntersectionSimilarity.Par
make() - Method in class elki.similarity.cluster.ClusterJaccardSimilarity.Par
make() - Method in class elki.similarity.kernel.LaplaceKernel.Par
make() - Method in class elki.similarity.kernel.LinearKernel.Par
make() - Method in class elki.similarity.kernel.PolynomialKernel.Par
make() - Method in class elki.similarity.kernel.RadialBasisFunctionKernel.Par
make() - Method in class elki.similarity.kernel.RationalQuadraticKernel.Par
make() - Method in class elki.similarity.kernel.SigmoidKernel.Par
make() - Method in class elki.similarity.Kulczynski1Similarity.Par
make() - Method in class elki.similarity.Kulczynski2Similarity.Par
make() - Method in class elki.timeseries.OfflineChangePointDetectionAlgorithm.Par
make() - Method in class elki.timeseries.SigniTrendChangeDetection.Par
make() - Method in interface elki.utilities.datastructures.histogram.ObjHistogram.BucketFactory
make() - Method in class elki.utilities.ensemble.EnsembleVotingInverseMultiplicative.Par
make() - Method in class elki.utilities.ensemble.EnsembleVotingMedian.Par
make() - Method in class elki.utilities.ensemble.EnsembleVotingMultiplicative.Par
make() - Method in interface elki.utilities.optionhandling.Parameterizer: Make an instance after successful configuration.
make() - Method in class elki.utilities.referencepoints.AxisBasedReferencePoints.Par
make() - Method in class elki.utilities.referencepoints.GridBasedReferencePoints.Par
make() - Method in class elki.utilities.referencepoints.RandomGeneratedReferencePoints.Par
make() - Method in class elki.utilities.referencepoints.RandomSampleReferencePoints.Par
make() - Method in class elki.utilities.referencepoints.StarBasedReferencePoints.Par
make() - Method in class elki.utilities.scaling.ClipScaling.Par
make() - Method in class elki.utilities.scaling.GammaScaling.Par
make() - Method in class elki.utilities.scaling.outlier.COPOutlierScaling.Par
make() - Method in class elki.utilities.scaling.outlier.MinusLogGammaScaling.Par
make() - Method in class elki.utilities.scaling.outlier.MinusLogStandardDeviationScaling.Par
make() - Method in class elki.utilities.scaling.outlier.OutlierGammaScaling.Par
make() - Method in class elki.utilities.scaling.outlier.OutlierLinearScaling.Par
make() - Method in class elki.utilities.scaling.outlier.OutlierSqrtScaling.Par
make() - Method in class elki.utilities.scaling.outlier.SqrtStandardDeviationScaling.Par
make() - Method in class elki.utilities.scaling.outlier.StandardDeviationScaling.Par
make() - Method in class elki.utilities.scaling.outlier.TopKOutlierScaling.Par
make() - Method in class elki.visualization.parallel3d.layout.CompactCircularMSTLayout3DPC.Par
make() - Method in class elki.visualization.parallel3d.layout.MultidimensionalScalingMSTLayout3DPC.Par
make() - Method in class elki.visualization.parallel3d.layout.SimpleCircularMSTLayout3DPC.Par
make() - Method in class elki.visualization.projector.HistogramFactory.Par
make() - Method in class elki.visualization.projector.ScatterPlotFactory.Par
make() - Method in class elki.visualization.VisualizerParameterizer.Par
make() - Method in class elki.visualization.visualizers.histogram.ColoredHistogramVisualizer.Par
make() - Method in class elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization.Par
make() - Method in class elki.visualization.visualizers.parallel.index.RTreeParallelVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.cluster.ClusterAlphaHullVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.cluster.ClusterConvexHullVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.index.TreeMBRVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.outlier.BubbleVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization.Par
make() - Method in class elki.visualization.visualizers.scatterplot.TooltipScoreVisualization.Par
make() - Method in class elki.visualization.visualizers.visunproj.DendrogramVisualization.Par
make() - Method in class elki.workflow.AlgorithmStep.Par
make() - Method in class elki.workflow.EvaluationStep.Par
make() - Method in class elki.workflow.InputStep.Par
make() - Method in class elki.workflow.LoggingStep.Par
make() - Method in class elki.workflow.OutputStep.Par
make() - Method in class tutorial.clustering.CFSFDP.Par
make() - Method in class tutorial.clustering.SameSizeKMeans.Par
make() - Method in class tutorial.distancefunction.MultiLPNorm.Par
make(int) - Method in class elki.index.tree.betula.features.BIRCHCF.Factory
make(int) - Method in interface elki.index.tree.betula.features.ClusterFeature.Factory: Make a new clustering feature of the given dimensionality.
make(int) - Method in class elki.index.tree.betula.features.VIIFeature.Factory
make(int) - Method in class elki.index.tree.betula.features.VVIFeature.Factory
make(int) - Method in class elki.index.tree.betula.features.VVVFeature.Factory
make(int) - Static method in class elki.math.SinCosTable: Make a table for the given number of steps.
make(int, long) - Static method in class elki.utilities.datastructures.BitsUtil: Allocate a new long[].
make(long[], Relation<? extends NumberVector>) - Static method in class elki.math.linearalgebra.ProjectedCentroid: Static Constructor from a relation.
make(long[], Relation<? extends NumberVector>, DBIDs) - Static method in class elki.math.linearalgebra.ProjectedCentroid: Static Constructor from a relation.
make(StaticDBIDs) - Static method in class elki.utilities.datastructures.unionfind.UnionFindUtil: Make a new instance (automatically choosing the best implementation).
make(Relation<? extends NumberVector>) - Static method in class elki.math.linearalgebra.CovarianceMatrix: Static Constructor from a full relation.
make(Relation<? extends NumberVector>, DBIDs) - Static method in class elki.math.linearalgebra.Centroid: Static constructor from an existing relation.
make(Relation<? extends NumberVector>, DBIDs) - Static method in class elki.math.linearalgebra.CovarianceMatrix: Static Constructor from a full relation.
make(Parameterizer, Parameterization) - Static method in class elki.utilities.ClassGenericsUtil: Method to configure a class, then instantiate when the configuration step was successful.
make(Collection<String>) - Static method in class elki.data.LabelList: Constructor replacement.
makeArffTokenizer(BufferedReader) - Method in class elki.datasource.parser.ArffParser: Make a StreamTokenizer for the ARFF format.
makeArrow(SVGPlot, SVGArrow.Direction, double, double, double) - Static method in class elki.visualization.svg.SVGArrow: Draw an arrow at the given position.
makeAWTImage(int, int) - Method in class elki.visualization.svg.SVGPlot: Convert the SVG to a thumbnail image.
makeButtonForVisible(int, int) - Method in class elki.visualization.visualizers.parallel.AxisVisibilityVisualization.Instance: Make a button for a visible axis
makeButtonsForHidden(int, int, int, int) - Method in class elki.visualization.visualizers.parallel.AxisVisibilityVisualization.Instance: Insert buttons for hidden dimensions.
makeCheckmark(SVGPlot) - Static method in class elki.visualization.svg.SVGEffects: Creates a 15x15 big checkmark
makeClockwise(List<double[]>) - Method in class elki.math.geometry.SweepHullDelaunay2D.Triangle: Make the triangle clockwise
makeCluster(int, double, DBIDs) - Method in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Instance: Make the cluster for the given object
makeCluster(int, DBIDs) - Method in class elki.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance: Make the cluster for the given object
makeCluster(Relation<? extends NumberVector>, DBIDs, long[]) - Method in class elki.clustering.subspace.DOC: Utility method to create a subspace cluster from a list of DBIDs and the relevant attributes.
makeClusterMap(ArrayDBIDs, int[]) - Method in class elki.clustering.affinitypropagation.AffinityPropagation: Build an int to DBIDs lookup for the clusters.
makeConfigurator(Parameter<?>) - Method in class elki.gui.configurator.ConfiguratorPanel
makeCoverTree(Relation<? extends O>, Distance<? super O>, int) - Method in class elki.database.query.EmpiricalQueryOptimizer
makeCurve() - Method in class elki.math.geometry.XYPlot: Make a new curve.
makeCurve(int) - Method in class elki.math.geometry.XYPlot: Make a new curve with desired color.
makeCurve(int, int) - Method in class elki.math.geometry.XYPlot: Make a new curve with desired color.
makeDBIDStorage(DBIDs, int) - Method in interface elki.database.datastore.DataStoreFactory: Make a new storage, to associate the given ids with an object of class dataclass.
makeDBIDStorage(DBIDs, int) - Static method in class elki.database.datastore.DataStoreUtil: Make a new storage, to associate the given ids with an object of class dataclass.
makeDBIDStorage(DBIDs, int) - Method in class elki.database.datastore.memory.MemoryDataStoreFactory
makeDescription(Cluster<?>) - Method in class elki.result.KMLOutputHandler: Make an HTML description.
makeDescription(Collection<Relation<?>>, DBIDRef) - Method in class elki.result.KMLOutputHandler: Make an HTML description.
makeDetailView() - Method in class elki.visualization.gui.overview.DetailViewSelectedEvent: Retrieve a materialized detail plot.
makeDetailView(PlotItem) - Method in class elki.visualization.gui.overview.OverviewPlot: Event triggered when a plot was selected.
makeDoubleStorage(DBIDs, int) - Method in interface elki.database.datastore.DataStoreFactory: Make a new storage, to associate the given ids with an object of class dataclass.
makeDoubleStorage(DBIDs, int) - Static method in class elki.database.datastore.DataStoreUtil: Make a new storage, to associate the given ids with an object of class dataclass.
makeDoubleStorage(DBIDs, int) - Method in class elki.database.datastore.memory.MemoryDataStoreFactory
makeDoubleStorage(DBIDs, int, double) - Method in interface elki.database.datastore.DataStoreFactory: Make a new storage, to associate the given ids with an object of class dataclass.
makeDoubleStorage(DBIDs, int, double) - Static method in class elki.database.datastore.DataStoreUtil: Make a new storage, to associate the given ids with an object of class dataclass.
makeDoubleStorage(DBIDs, int, double) - Method in class elki.database.datastore.memory.MemoryDataStoreFactory
makeElement(SVGPlot) - Method in class elki.visualization.svg.SVGPath: Turn the path buffer into an SVG element.
makeElement(SVGPlot, String) - Method in class elki.visualization.svg.SVGPath: Turn the path buffer into an SVG element.
makeFolds(int, int) - Static method in class elki.svm.AbstractSingleSVM
makeFromString(String) - Method in class elki.data.ClassLabel.Factory: Convert a string into a class label.
makeFromString(String) - Method in class elki.data.HierarchicalClassLabel.Factory
makeFromString(String) - Method in class elki.data.SimpleClassLabel.Factory
makeGradient(int, String[]) - Method in class elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance: Creates a gradient over a set of colors
makeHull(double[][]) - Method in class elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance: Build a convex hull to approximate the sphere.
makeHullComplex(double[][]) - Method in class elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance: Build a convex hull to approximate the sphere.
makeIndividuum(short[]) - Method in class elki.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch: Make a new individuum helper, computing sparsity=fitness
makeIntegerStorage(DBIDs, int) - Method in interface elki.database.datastore.DataStoreFactory: Make a new storage, to associate the given ids with an object of class dataclass.
makeIntegerStorage(DBIDs, int) - Static method in class elki.database.datastore.DataStoreUtil: Make a new storage, to associate the given ids with an object of class dataclass.
makeIntegerStorage(DBIDs, int) - Method in class elki.database.datastore.memory.MemoryDataStoreFactory
makeIntegerStorage(DBIDs, int, int) - Method in interface elki.database.datastore.DataStoreFactory: Make a new storage, to associate the given ids with an object of class dataclass.
makeIntegerStorage(DBIDs, int, int) - Static method in class elki.database.datastore.DataStoreUtil: Make a new storage, to associate the given ids with an object of class dataclass.
makeIntegerStorage(DBIDs, int, int) - Method in class elki.database.datastore.memory.MemoryDataStoreFactory
makeInvisible() - Method in class elki.visualization.batikutil.DragableArea: Make the rectangle invisible.
makeKDTree(Relation<? extends O>, Distance<? super O>, int) - Method in class elki.database.query.EmpiricalQueryOptimizer
makeKey(int, int) - Static method in class elki.distance.external.FileBasedSparseDoubleDistance: Combine two integer ids into a long value.
makeKey(int, int) - Static method in class elki.distance.external.FileBasedSparseFloatDistance: Combine two integer ids into a long value.
makeKnnPreprocessor(Relation<? extends O>, DistanceQuery<O>, int, int) - Method in class elki.database.query.EmpiricalQueryOptimizer: Make a knn preprocessor.
makeLayerElement() - Method in class elki.visualization.visualizers.optics.AbstractOPTICSVisualization: Produce a new layer element.
makeLayerElement() - Method in class elki.visualization.visualizers.silhouette.AbstractSilhouetteVisualization: Produce a new layer element.
makeMarginTransform(double, double, double, double, double) - Static method in class elki.visualization.svg.SVGUtil: Make a transform string to add margins
makeMarginTransform(double, double, double, double, double, double) - Static method in class elki.visualization.svg.SVGUtil: Make a transform string to add margins
makeMarginTransform(double, double, double, double, double, double, double, double) - Static method in class elki.visualization.svg.SVGUtil: Make a transform string to add margins
makeMatrixIndex(Relation<? extends O>, Distance<? super O>) - Method in class elki.database.query.EmpiricalQueryOptimizer
makeMenuItemForVisualizer(Object) - Method in class elki.visualization.gui.ResultWindow.DynamicMenu
makeModel() - Method in interface elki.data.synthetic.bymodel.GeneratorInterface: Make a cluster model for this cluster.
makeModel() - Method in class elki.data.synthetic.bymodel.GeneratorSingleCluster
makeModel() - Method in class elki.data.synthetic.bymodel.GeneratorStatic
makeNode(int, List<CompactCircularMSTLayout3DPC.Node>) - Method in class elki.visualization.parallel3d.layout.CompactCircularMSTLayout3DPC
makeNode(int, List<MultidimensionalScalingMSTLayout3DPC.Node>) - Method in class elki.visualization.parallel3d.layout.MultidimensionalScalingMSTLayout3DPC
makeNode(int, List<SimpleCircularMSTLayout3DPC.Node>) - Method in class elki.visualization.parallel3d.layout.SimpleCircularMSTLayout3DPC
makeNode(int, List<N>) - Method in class elki.visualization.parallel3d.layout.AbstractLayout3DPC
makeNumberFormat(int) - Static method in class elki.utilities.io.FormatUtil: Initialize a number format with ELKI standard options (US locale, no grouping).
makeObject() - Method in class elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram: Make a new empty bucket for the data store.
makeOPTICSCut(E, double) - Static method in class elki.visualization.opticsplot.OPTICSCut: Compute an OPTICS cut clustering
makeOrUpdateSegment(int[], DBIDs, int) - Method in class elki.evaluation.clustering.pairsegments.Segments
makePageFile(Class<N>) - Method in class elki.index.PagedIndexFactory: Make the page file for this index.
makePopulationMatrix() - Method in class elki.math.linearalgebra.CovarianceMatrix: Obtain the covariance matrix according to the population statistics: n degrees of freedom.
makeReader() - Method in class elki.datasource.parser.CSVReaderFormat: Make a reader for the configured format.
makeRecordStorage(DBIDs, int, Class<?>...) - Method in interface elki.database.datastore.DataStoreFactory: Make a new record storage, to associate the given ids with an object of class dataclass.
makeRecordStorage(DBIDs, int, Class<?>...) - Static method in class elki.database.datastore.DataStoreUtil: Make a new record storage, to associate the given ids with an object of class dataclass.
makeRecordStorage(DBIDs, int, Class<?>...) - Method in class elki.database.datastore.memory.MemoryDataStoreFactory
makeRunnerIfNeeded() - Method in class elki.visualization.batikutil.JSVGUpdateSynchronizer: Join the runnable queue of a component.
makeSample(int) - Method in class elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators: Generate a data sample.
makeSampleMatrix() - Method in class elki.math.linearalgebra.CovarianceMatrix: Obtain the covariance matrix according to the sample statistics: (n-1) degrees of freedom.
makeSettings() - Method in class elki.index.tree.metrical.mtreevariants.AbstractMTreeFactory.Par
makeSettings() - Method in class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeFactory.Par
makeSimple(SimpleTypeInformation<? super V>, List<? extends V>) - Static method in class elki.datasource.bundle.MultipleObjectsBundle: Helper to add a single column to the bundle.
makeSimple(SimpleTypeInformation<? super V1>, List<? extends V1>, SimpleTypeInformation<? super V2>, List<? extends V2>) - Static method in class elki.datasource.bundle.MultipleObjectsBundle: Helper to add a single column to the bundle.
makeSimple(SimpleTypeInformation<? super V1>, List<? extends V1>, SimpleTypeInformation<? super V2>, List<? extends V2>, SimpleTypeInformation<? super V3>, List<? extends V3>) - Static method in class elki.datasource.bundle.MultipleObjectsBundle: Helper to add a single column to the bundle.
makeStats(KDTreeEM.KDTree, int[], WritableDataStore<double[]>) - Method in class elki.clustering.em.KDTreeEM: Calculates the statistics on the kd-tree needed for the calculation of the new models
makeStorage(DBIDs, int, Class<? super T>) - Method in interface elki.database.datastore.DataStoreFactory: Make a new storage, to associate the given ids with an object of class dataclass.
makeStorage(DBIDs, int, Class<? super T>) - Static method in class elki.database.datastore.DataStoreUtil: Make a new storage, to associate the given ids with an object of class dataclass.
makeStorage(DBIDs, int, Class<? super T>) - Method in class elki.database.datastore.memory.MemoryDataStoreFactory
makeStyleElement(Document) - Method in class elki.visualization.css.CSSClassManager: Make a (filled) CSS style element for the given document.
makeStyleElement(Document) - Static method in class elki.visualization.svg.SVGUtil: Make a new CSS style element for the given Document.
makeStyleResult(StyleLibrary) - Method in class elki.visualization.VisualizerContext: Generate a new style result for the given style library.
makeTooltip(DBIDRef, double, double, double) - Method in class elki.visualization.visualizers.scatterplot.AbstractTooltipVisualization: Make a tooltip Element for this id.
makeTooltip(DBIDRef, double, double, double) - Method in class elki.visualization.visualizers.scatterplot.TooltipScoreVisualization.Instance
makeTooltip(DBIDRef, double, double, double) - Method in class elki.visualization.visualizers.scatterplot.TooltipStringVisualization.Instance
makeUnmodifiable(DBIDs) - Method in interface elki.database.ids.DBIDFactory: Make DBIDs immutable.
makeUnmodifiable(DBIDs) - Static method in class elki.database.ids.DBIDUtil: Wrap an existing DBIDs collection to be unmodifiable.
makeUnmodifiable(DBIDs) - Method in class elki.database.ids.integer.AbstractIntegerDBIDFactory
makeVisible() - Method in class elki.visualization.batikutil.DragableArea: Make the rectangle visible, for debug purposes.
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.actions.ClusterStyleAction
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.histogram.ColoredHistogramVisualizer
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.optics.OPTICSClusterVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.optics.OPTICSPlotCutVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.optics.OPTICSPlotVisualizer
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.optics.OPTICSSteepAreaVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.AxisReorderVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.AxisVisibilityVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.BoundingBoxVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.cluster.ClusterParallelMeanVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.index.RTreeParallelVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.LineVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.ParallelAxisVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.selection.SelectionAxisRangeVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.selection.SelectionLineVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.AxisVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.cluster.ClusterAlphaHullVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.cluster.ClusterConvexHullVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.cluster.ClusterMeanVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.cluster.ClusterOrderVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.cluster.ClusterStarVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.density.DensityEstimationOverlay
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.index.TreeMBRVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.MarkerVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.outlier.BubbleVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.outlier.COPVectorVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.PolygonVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.ReferencePointsVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.selection.DistanceFunctionVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.selection.SelectionConvexHullVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.selection.SelectionDotVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.TooltipScoreVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.TooltipStringVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.uncertain.UncertainBoundingBoxVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.uncertain.UncertainInstancesVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.scatterplot.uncertain.UncertainSamplesVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.silhouette.SilhouettePlotSelectionToolVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.silhouette.SilhouettePlotSelectionVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.silhouette.SilhouettePlotVisualizer
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in interface elki.visualization.visualizers.VisFactory: Produce a visualization instance for the given task
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.DendrogramVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.EvaluationVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.HistogramVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.KeyVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.LabelVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.PixmapVisualizer
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.SettingsVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.SimilarityMatrixVisualizer
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.XYCurveVisualization
makeVisualization(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection) - Method in class elki.visualization.visualizers.visunproj.XYPlotVisualization
makeVisualizationOrThumbnail(VisualizerContext, VisualizationTask, VisualizationPlot, double, double, Projection, int) - Method in interface elki.visualization.visualizers.VisFactory: Produce a visualization instance for the given task that may use thumbnails
makeVPTree(Relation<? extends O>, Distance<? super O>, int) - Method in class elki.database.query.EmpiricalQueryOptimizer
manager - Variable in class elki.result.AutomaticVisualization: Visualization manager.
manager - Variable in class elki.result.AutomaticVisualization.Par: Visualization manager.
manager - Variable in class elki.result.ExportVisualizations: Visualization manager.
manager - Variable in class elki.result.ExportVisualizations.Par: Visualization manager.
managerStarted(UpdateManagerEvent) - Method in class elki.visualization.batikutil.JSVGUpdateSynchronizer.UMAdapter: React to an update manager becoming available.
managerStopped(UpdateManagerEvent) - Method in class elki.visualization.batikutil.JSVGUpdateSynchronizer.UMAdapter
MANHATTAN - elki.application.greedyensemble.GreedyEnsembleExperiment.Distance
MANHATTAN - elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization.Mode
ManhattanDistance - Class in elki.distance.minkowski: Manhattan distance for NumberVectors.
ManhattanDistance() - Constructor for class elki.distance.minkowski.ManhattanDistance: Deprecated.
Use static instance!
ManhattanDistance.Par - Class in elki.distance.minkowski: Parameterization class.
ManhattanHashFunctionFamily - Class in elki.index.lsh.hashfamilies: 2-stable hash function family for Euclidean distances.
ManhattanHashFunctionFamily(RandomFactory, double, int) - Constructor for class elki.index.lsh.hashfamilies.ManhattanHashFunctionFamily: Constructor.
ManhattanHashFunctionFamily.Par - Class in elki.index.lsh.hashfamilies: Parameterization class.
manhattanSegmentalDistance(NumberVector, double[], long[]) - Method in class elki.clustering.subspace.PROCLUS: Returns the Manhattan segmental distance between o1 and o2 relative to the specified dimensions.
manhattanSegmentalDistance(NumberVector, NumberVector, long[]) - Method in class elki.clustering.subspace.PROCLUS: Returns the Manhattan segmental distance between o1 and o2 relative to the specified dimensions.
map - Variable in class elki.algorithm.statistics.EvaluateRetrievalPerformance.RetrievalPerformanceResult: MAP value
map - Variable in class elki.database.datastore.memory.MapIntegerDBIDDBIDStore: Data storage.
map - Variable in class elki.database.datastore.memory.MapIntegerDBIDDoubleStore: Data storage.
map - Variable in class elki.database.datastore.memory.MapIntegerDBIDIntegerStore: Data storage.
map - Variable in class elki.datasource.filter.normalization.instancewise.LengthNormalization: Map used if converting sparse vectors.
map - Variable in class elki.persistent.LRUCache: The map holding the objects of this cache.
map - Variable in class elki.persistent.OnDiskArray: The memory mapped buffer.
map - Variable in class elki.visualization.gui.overview.LayerMap: The actual map
map - Variable in class elki.visualization.gui.overview.RectangleArranger: Data
map(DBIDRef) - Method in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Instance.Mapper
map(DBIDRef) - Method in class elki.clustering.kmeans.parallel.KMeansProcessor.Instance
map(DBIDRef) - Method in class elki.outlier.distance.parallel.KNNWeightProcessor.Instance
map(DBIDRef) - Method in class elki.outlier.lof.parallel.LOFProcessor.Instance
map(DBIDRef) - Method in class elki.outlier.lof.parallel.LRDProcessor.Instance
map(DBIDRef) - Method in class elki.outlier.lof.parallel.SimplifiedLRDProcessor.Instance
map(DBIDRef) - Method in class elki.parallel.processor.AbstractDoubleProcessor.Instance
map(DBIDRef) - Method in class elki.parallel.processor.DoubleMinMaxProcessor.Instance
map(DBIDRef) - Method in class elki.parallel.processor.KDistanceProcessor.Instance
map(DBIDRef) - Method in class elki.parallel.processor.KNNProcessor.Instance
map(DBIDRef) - Method in interface elki.parallel.processor.Processor.Instance: Process ("map") a single object
map(DBIDRef) - Method in class elki.parallel.processor.WriteDataStoreProcessor.Instance
map(DBIDRef) - Method in class elki.parallel.processor.WriteDoubleDataStoreProcessor.Instance
map(DBIDRef) - Method in class elki.parallel.processor.WriteIntegerDataStoreProcessor.Instance
map(DoubleUnaryOperator) - Method in class elki.database.ids.integer.DoubleIntegerDBIDKNNList
map(DoubleUnaryOperator) - Method in class elki.database.ids.integer.IntegerDBIDKNNSubList
map(DoubleUnaryOperator) - Method in interface elki.database.ids.KNNList: Function to project the knn list.
mapArray() - Method in class elki.persistent.OnDiskArray: (Re-) map the data array.
mapDBIDToOffset(DBIDRef) - Method in interface elki.database.datastore.DataStoreIDMap: Map a DBID to an array offset.
mapDBIDToOffset(DBIDRef) - Method in class elki.database.ids.integer.IntegerDBIDRange
MapIntegerDBIDDBIDStore - Class in elki.database.datastore.memory: Writable data store for double values.
MapIntegerDBIDDBIDStore(int) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDDBIDStore: Constructor.
MapIntegerDBIDDoubleStore - Class in elki.database.datastore.memory: Writable data store for double values.
MapIntegerDBIDDoubleStore(int) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDDoubleStore: Constructor.
MapIntegerDBIDDoubleStore(int, double) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDDoubleStore: Constructor.
MapIntegerDBIDIntegerStore - Class in elki.database.datastore.memory: Writable data store for double values.
MapIntegerDBIDIntegerStore(int) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDIntegerStore: Constructor.
MapIntegerDBIDIntegerStore(int, int) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDIntegerStore: Constructor.
MapIntegerDBIDRecordStore - Class in elki.database.datastore.memory: A class to answer representation queries using a map and an index within the record.
MapIntegerDBIDRecordStore(int) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDRecordStore: Constructor without existing data.
MapIntegerDBIDRecordStore(int, int) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDRecordStore: Constructor without existing data.
MapIntegerDBIDRecordStore(int, Int2ObjectMap<Object[]>) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDRecordStore: Constructor with existing data.
MapIntegerDBIDRecordStore.StorageAccessor<T> - Class in elki.database.datastore.memory: Access a single record in the given data.
MapIntegerDBIDStore<T> - Class in elki.database.datastore.memory: A class to answer representation queries using a map.
MapIntegerDBIDStore() - Constructor for class elki.database.datastore.memory.MapIntegerDBIDStore: Constructor.
MapIntegerDBIDStore(int) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDStore: Constructor.
MapIntegerDBIDStore(Int2ObjectMap<T>) - Constructor for class elki.database.datastore.memory.MapIntegerDBIDStore: Constructor.
mapMouseToPlane(Simple1DOFCamera, Point, double[]) - Method in class elki.visualization.parallel3d.util.Arcball1DOFAdapter: Map the coordinates.
Mapper(NeighborPredicate.Instance<? extends T>) - Constructor for class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Instance.Mapper: Constructor.
MapRecordStore - Class in elki.database.datastore.memory: A class to answer representation queries using a map and an index within the record.
MapRecordStore(int) - Constructor for class elki.database.datastore.memory.MapRecordStore: Constructor without existing data.
MapRecordStore(int, Map<DBID, Object[]>) - Constructor for class elki.database.datastore.memory.MapRecordStore: Constructor with existing data.
MapRecordStore.StorageAccessor<T> - Class in elki.database.datastore.memory: Access a single record in the given data.
MapStore<T> - Class in elki.database.datastore.memory: A class to answer representation queries using a map.
MapStore() - Constructor for class elki.database.datastore.memory.MapStore: Constructor.
MapStore(Map<DBID, T>) - Constructor for class elki.database.datastore.memory.MapStore: Constructor.
MARGIN - Static variable in interface elki.visualization.style.StyleLibrary: Margin
margins - Variable in class elki.visualization.visualizers.parallel.AbstractParallelVisualization: margin
markAsAssigned() - Method in class elki.clustering.subspace.clique.CLIQUEUnit: Marks this unit as assigned to a cluster.
MARKER - Static variable in class elki.visualization.visualizers.parallel.selection.SelectionAxisRangeVisualization.Instance: CSS Class for the range marker
MARKER - Static variable in class elki.visualization.visualizers.parallel.selection.SelectionLineVisualization.Instance: CSS Class for the range marker
MARKER - Static variable in class elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization.Instance: Generic tag to indicate the type of element.
MARKER - Static variable in class elki.visualization.visualizers.scatterplot.selection.SelectionDotVisualization.Instance: Generic tag to indicate the type of element.
markerlib - Variable in class elki.visualization.style.PropertiesBasedStyleLibrary: Marker library to use
MarkerLibrary - Interface in elki.visualization.style.marker: A marker library is a class that can generate and draw various styles of markers.
MARKERPLOT - Static variable in interface elki.visualization.style.StyleLibrary: Marker size
markers() - Method in class elki.visualization.style.PropertiesBasedStyleLibrary
markers() - Method in interface elki.visualization.style.StyleLibrary: Get the marker library to use.
MarkerVisualization - Class in elki.visualization.visualizers.scatterplot: Visualize a clustering using different markers for different clusters.
MarkerVisualization() - Constructor for class elki.visualization.visualizers.scatterplot.MarkerVisualization: Constructor.
MarkerVisualization.Instance - Class in elki.visualization.visualizers.scatterplot: Instance.
mask - Static variable in class elki.utilities.random.FastNonThreadsafeRandom
MASK32 - Static variable in class elki.index.lsh.hashfunctions.MultipleProjectionsLocalitySensitiveHashFunction: Bit mask for signed int to unsigned long conversion.
maskMatrix(double[][], Distribution, Random) - Method in class elki.clustering.biclustering.ChengAndChurch.BiclusterCandidate: Updates the mask with replacement values for all data in the given rows and columns.
MASTER_CACHE - Static variable in class elki.utilities.ELKIServiceScanner: (Non-weak) cache for all "frequently scanned" classes.
mat - Variable in class elki.clustering.hierarchical.AGNES.Instance: Cluster distance matrix
mat - Variable in class elki.data.projection.random.SimplifiedRandomHyperplaneProjectionFamily.SignedProjection: Projection matrix.
mat - Variable in class elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Instance.Shared: Current similarity matrix.
match(Object, Object) - Static method in class elki.algorithm.statistics.AveragePrecisionAtK: Test whether two relation agree.
match(Object, Object) - Static method in class elki.algorithm.statistics.EvaluateRetrievalPerformance: Test whether two relation agree.
matcher - Variable in class elki.datasource.filter.selection.ByLabelFilter: The filter pattern matcher
matcher - Variable in class elki.utilities.io.Tokenizer: Regular expression match helper.
matchInf(byte[], byte, int, int) - Static method in class elki.utilities.io.ParseUtil: Match "inf", "infinity" in a number of different capitalizations.
matchInf(CharSequence, char, int, int) - Static method in class elki.utilities.io.ParseUtil: Match "inf", "infinity" in a number of different capitalizations.
matchNaN(byte[], byte, int, int) - Static method in class elki.utilities.io.ParseUtil: Match "NaN" in a number of different capitalizations.
matchNaN(CharSequence, char, int, int) - Static method in class elki.utilities.io.ParseUtil: Match "NaN" in a number of different capitalizations.
materialize - Variable in class elki.index.projected.ProjectedIndex.Factory: Whether to use a materialized view, or a virtual view.
materialize() - Method in class elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram: Materialize the histogram from the cache.
materialize() - Method in class elki.utilities.datastructures.histogram.DoubleDynamicHistogram: Materialize the histogram from the cache.
MaterializedDoubleRelation - Class in elki.database.relation: Represents a single representation.
MaterializedDoubleRelation(String, DBIDs) - Constructor for class elki.database.relation.MaterializedDoubleRelation: Constructor.
MaterializedDoubleRelation(String, DBIDs, DoubleDataStore) - Constructor for class elki.database.relation.MaterializedDoubleRelation: Constructor.
MaterializedRelation<O> - Class in elki.database.relation: Represents a single representation.
MaterializedRelation(SimpleTypeInformation<O>, DBIDs) - Constructor for class elki.database.relation.MaterializedRelation: Constructor.
MaterializedRelation(String, SimpleTypeInformation<O>, DBIDs) - Constructor for class elki.database.relation.MaterializedRelation: Constructor.
MaterializedRelation(String, SimpleTypeInformation<O>, DBIDs, DataStore<O>) - Constructor for class elki.database.relation.MaterializedRelation: Constructor.
MaterializeKNNAndRKNNPreprocessor<O> - Class in elki.index.preprocessed.knn: A preprocessor for annotation of the k nearest neighbors and the reverse k nearest neighbors (and their distances) to each database object.
MaterializeKNNAndRKNNPreprocessor(Relation<O>, Distance<? super O>, int) - Constructor for class elki.index.preprocessed.knn.MaterializeKNNAndRKNNPreprocessor: Constructor.
MaterializeKNNAndRKNNPreprocessor.Factory<O> - Class in elki.index.preprocessed.knn: The parameterizable factory.
MaterializeKNNAndRKNNPreprocessor.Factory.Par<O> - Class in elki.index.preprocessed.knn: Parameterization class.
materializeKNNAndRKNNs(ArrayDBIDs, FiniteProgress) - Method in class elki.index.preprocessed.knn.MaterializeKNNAndRKNNPreprocessor: Materializes the kNNs and RkNNs of the specified object IDs.
MaterializeKNNPreprocessor<O> - Class in elki.index.preprocessed.knn: A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
MaterializeKNNPreprocessor(Relation<O>, DistanceQuery<O>, int, boolean) - Constructor for class elki.index.preprocessed.knn.MaterializeKNNPreprocessor: Constructor with preprocessing step.
MaterializeKNNPreprocessor(Relation<O>, Distance<? super O>, int) - Constructor for class elki.index.preprocessed.knn.MaterializeKNNPreprocessor: Constructor with preprocessing step.
MaterializeKNNPreprocessor.Factory<O> - Class in elki.index.preprocessed.knn: The parameterizable factory.
MaterializeKNNPreprocessor.Factory.Par<O> - Class in elki.index.preprocessed.knn: Parameterization class.
materializePRC(ScoreEvaluation.Adapter) - Static method in class elki.evaluation.scores.AUPRCEvaluation: Compute the PR curve given a predicate function and an iterator.
materializePRGC(ScoreEvaluation.Adapter) - Static method in class elki.evaluation.scores.PRGCEvaluation: Compute the PRG curve given a predicate function and an iterator.
materializeROC(ScoreEvaluation.Adapter) - Static method in class elki.evaluation.scores.ROCEvaluation: Compute a ROC curve given a set of positive IDs and a sorted list of (comparable, ID)s, where the comparable object is used to decided when two objects are interchangeable.
MathUtil - Class in elki.math: A collection of math related utility functions.
MathUtil() - Constructor for class elki.math.MathUtil: Fake constructor for static class.
matrix - Variable in class elki.clustering.hierarchical.ClusterDistanceMatrix: Distance matrix (modifiable).
matrix - Variable in class elki.data.projection.random.AbstractRandomProjectionFamily.MatrixProjection: Projection matrix.
matrix - Variable in class elki.index.distancematrix.PrecomputedDistanceMatrix: Distance matrix.
matrix - Variable in class elki.index.distancematrix.PrecomputedSimilarityMatrix: Similarity matrix.
matrix - Variable in class elki.index.tree.betula.CFDistanceMatrix: Distance matrix (serialized)
MATRIX - Static variable in class elki.data.type.TypeUtil: Matrix type.
MATRIX_ID - Static variable in class elki.distance.external.DiskCacheBasedDoubleDistance.Par: Parameter that specifies the name of the distance matrix file.
MATRIX_ID - Static variable in class elki.distance.external.DiskCacheBasedFloatDistance.Par: Parameter that specifies the name of the distance matrix file.
MATRIX_ID - Static variable in class elki.distance.external.FileBasedSparseDoubleDistance.Par: Parameter that specifies the name of the distance matrix file.
MATRIX_ID - Static variable in class elki.distance.external.FileBasedSparseFloatDistance.Par: Parameter that specifies the name of the distance matrix file.
matrixfile - Variable in class elki.distance.external.FileBasedSparseDoubleDistance: Input file of distance matrix
matrixfile - Variable in class elki.distance.external.FileBasedSparseDoubleDistance.Par: Input file.
matrixfile - Variable in class elki.distance.external.FileBasedSparseFloatDistance: Input file of distance matrix
matrixfile - Variable in class elki.distance.external.FileBasedSparseFloatDistance.Par: Input file.
matrixIndex - Variable in class elki.database.query.EmpiricalQueryOptimizer: Distance matrix index class.
MatrixProjection(double[][]) - Constructor for class elki.data.projection.random.AbstractRandomProjectionFamily.MatrixProjection: Constructor.
matrixsize - Variable in class elki.persistent.OnDiskUpperTriangleMatrix: Size of the matrix
MatrixWeightedQuadraticDistance - Class in elki.distance: Matrix weighted quadratic distance, the squared form of MahalanobisDistance.
MatrixWeightedQuadraticDistance(double[][]) - Constructor for class elki.distance.MatrixWeightedQuadraticDistance: Constructor.
matSelfInit(ClusterFeature) - Method in class elki.index.tree.betula.distance.AverageIntraclusterDistance
matSelfInit(ClusterFeature) - Method in interface elki.index.tree.betula.distance.CFDistance: Initialization for self measure for new Combinatorial clustering Methods (Podani 1989)
matSelfInit(ClusterFeature) - Method in class elki.index.tree.betula.distance.RadiusDistance
max - Variable in class elki.data.HyperBoundingBox: The coordinates of the 'upper right' (= maximum) hyper point.
max - Variable in class elki.data.spatial.Polygon: Maximum values
max - Variable in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization: Minimum and maximum values.
max - Variable in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization.Par: Minimum and maximum values.
max - Variable in class elki.distance.external.FileBasedSparseDoubleDistance: Minimum and maximum IDs seen.
max - Variable in class elki.distance.external.FileBasedSparseFloatDistance: Minimum and maximum IDs seen.
max - Variable in class elki.math.DoubleMinMax: Minimum and maximum.
max - Variable in class elki.math.IntegerMinMax: Minimum and maximum.
max - Variable in class elki.math.linearalgebra.ConstrainedQuadraticProblemSolver.ProblemData
max - Variable in class elki.math.MeanVarianceMinMax: Maximum value
max - Variable in class elki.math.scales.LinearScale: max value of the scale
max - Variable in class elki.math.statistics.distribution.HaltonUniformDistribution: Maximum
max - Variable in class elki.math.statistics.distribution.HaltonUniformDistribution.Par: Parameters.
max - Variable in class elki.math.statistics.distribution.UniformDistribution: Maximum
max - Variable in class elki.math.statistics.distribution.UniformDistribution.Par: Parameters.
max - Variable in class elki.outlier.density.IsolationForest.ForestBuilder: Current value range
max - Variable in class elki.result.EvaluationResult.Measurement: Observed value, minimum, maximum, expected value.
max - Variable in class elki.utilities.datastructures.histogram.AbstractStaticHistogram: To avoid introducing an extra bucket for the maximum value.
max - Variable in class elki.utilities.datastructures.range.CombinedIntGenerator: Maximum value.
max - Variable in class elki.utilities.datastructures.range.StaticIntGenerator: Maximum value.
max - Variable in class elki.utilities.scaling.ClipScaling: Field storing the maximum to use
max - Variable in class elki.utilities.scaling.ClipScaling.Par
max - Variable in class elki.utilities.scaling.outlier.MinusLogGammaScaling: Maximum value seen
max - Variable in class elki.utilities.scaling.outlier.OutlierLinearScaling: Field storing the Maximum value
max - Variable in class elki.utilities.scaling.outlier.OutlierLinearScaling.Par: Field storing the Maximum value
max - Variable in class elki.utilities.scaling.outlier.OutlierMinusLogScaling: Maximum value seen, set by OutlierMinusLogScaling.prepare(elki.result.outlier.OutlierResult)
max - Variable in class elki.utilities.scaling.outlier.OutlierSqrtScaling: Minimum and maximum values.
max - Variable in class elki.utilities.scaling.outlier.OutlierSqrtScaling.Par: Predefined maximum value.
max - Variable in class elki.utilities.scaling.outlier.TopKOutlierScaling: The maximum value
max - Variable in class elki.visualization.svg.SVGScoreBar: Value, minimum and maximum values
max(double[], double[]) - Method in class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree: Returns an array that holds the maximum values of the both specified arrays in each index.
max(double, double) - Static method in class elki.math.MathUtil: Binary max, without handling of special values.
max(double, double, double) - Static method in class elki.math.MathUtil: Ternary max, without handling of special values.
max(double, double, double, double) - Static method in class elki.math.MathUtil: Quadrary max, without handling of special values.
max(int, int) - Static method in class elki.math.MathUtil: Binary max.
max(int, int, int) - Static method in class elki.math.MathUtil: Ternary max.
max(int, int, int, int) - Static method in class elki.math.MathUtil: Quadrary max, without handling of special values.
max(Map<Integer, ModifiableDBIDs>) - Method in class elki.clustering.subspace.DiSH.Instance: Returns the set with the maximum size contained in the specified map.
MAX_ARRAY_SIZE - Static variable in class elki.utilities.datastructures.arraylike.DoubleArray: Maximum array size permitted by Java.
MAX_ARRAY_SIZE - Static variable in class elki.utilities.datastructures.arraylike.IntegerArray: Maximum array size permitted by Java.
MAX_ARRAY_SIZE - Static variable in class elki.utilities.datastructures.heap.HeapUtil: Maximum Java array size according to some sources.
MAX_DIMENSIONS_DEFAULT - Static variable in class elki.visualization.projector.ScatterPlotFactory: Maximum number of dimensions to visualize.
MAX_EM_ITERATIONS_ID - Static variable in class elki.clustering.subspace.P3C.Par: Maximum number of iterations for the EM step.
MAX_HEIGHT - Static variable in class elki.visualization.opticsplot.OPTICSPlot: Minimum and maximum vertical resolution.
MAX_HEIGHT - Static variable in class elki.visualization.silhouette.SilhouettePlot: Minimum and maximum vertical resolution.
MAX_ID - Static variable in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization.Par: Option ID for maximum value.
MAX_ID - Static variable in class elki.math.statistics.distribution.UniformDistribution.Par: Maximum value
MAX_ID - Static variable in class elki.utilities.scaling.ClipScaling: Parameter to specify the maximum value
MAX_ID - Static variable in class elki.utilities.scaling.outlier.OutlierLinearScaling.Par: Parameter to specify the maximum value.
MAX_ID - Static variable in class elki.utilities.scaling.outlier.OutlierSqrtScaling.Par: Parameter to specify the fixed maximum to use.
MAX_INTERSECTION - elki.clustering.subspace.DiSH.Strategy: Max intersection strategy.
MAX_ITER - Static variable in class elki.math.geodesy.AbstractEarthModel: Maximum number of iterations.
MAX_ITER - Static variable in class elki.math.geodesy.SphereUtil: Maximum number of iterations.
MAX_ITER - Static variable in class elki.outlier.GaussianUniformMixture: Maximum number of iterations to do.
MAX_ITERATIONS - Static variable in class elki.math.statistics.distribution.GammaDistribution: Maximum number of iterations for regularizedGammaP.
MAX_ITERATIONS - Static variable in class elki.outlier.subspace.AggarwalYuEvolutionary: Maximum iteration count for evolutionary search.
MAX_K_ID - Static variable in class elki.evaluation.outlier.OutlierPrecisionAtKCurve.Par: Maximum value for k
MAX_RETRIES - Static variable in class elki.outlier.meta.HiCS: Maximum number of retries.
MAX2QUOTIENT - elki.visualization.style.ClusterStylingPolicy.IntensityTransform
MAX2QUOTIENTQUAD - elki.visualization.style.ClusterStylingPolicy.IntensityTransform
MAX2SUBTRACT - elki.visualization.style.ClusterStylingPolicy.IntensityTransform
maxClusterSize(int[][], int, int) - Static method in class elki.evaluation.clustering.Entropy: Get the maximum cluster size of a contingency table.
maxdepth - Variable in class elki.clustering.kmeans.initialization.betula.CFKPlusPlusTree: Maximum depth to choose at.
maxDepth(Layout.Node) - Method in class elki.visualization.parallel3d.layout.AbstractLayout3DPC: Compute the depth of the graph.
maxDev - Variable in class elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier: Minimum and maximum allowed deviation.
maxDev - Variable in class elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier.Par: Minimum and maximum allowed deviation.
maxDev - Variable in class elki.data.uncertain.uncertainifier.UniformUncertainifier: Minimum and maximum allowed deviation.
maxDev - Variable in class elki.data.uncertain.uncertainifier.UniformUncertainifier.Par: Minimum and maximum allowed deviation.
maxdim - Variable in class elki.clustering.correlation.LMCLUS.Par: Maximum dimensionality to search for
maxdim - Variable in class elki.data.type.VectorTypeInformation: Maximum dimensionality.
maxdim - Variable in class elki.datasource.filter.typeconversions.SparseVectorFieldFilter: Maximum dimension.
maxdim - Variable in class elki.datasource.parser.NumberVectorLabelParser: Dimensionality reported.
maxdim - Variable in class elki.visualization.projector.HistogramFactory: Maximum dimensionality.
maxdim - Variable in class elki.visualization.projector.HistogramFactory.Par: Stores the maximum number of dimensions to show.
maxdim - Variable in class elki.visualization.projector.ScatterPlotFactory: Stores the maximum number of dimensions to show.
maxdim - Variable in class elki.visualization.projector.ScatterPlotFactory.Par: Stores the maximum number of dimensions to show.
maxdim() - Method in class elki.data.type.VectorTypeInformation: Get the maximum dimensionality of the occurring vectors.
MAXDIM_ID - Static variable in class elki.clustering.correlation.LMCLUS.Par: Parameter with the maximum dimension to search for
MAXDIM_ID - Static variable in class elki.visualization.projector.ScatterPlotFactory.Par: Parameter for the maximum number of dimensions.
maxDimensionality(Relation<? extends SpatialComparable>) - Static method in class elki.database.relation.RelationUtil: Get the dimensionality of a database relation.
maxDist - Variable in class elki.index.tree.metrical.covertree.CoverTree.Node: Maximum distance to descendants.
maxDist - Variable in class elki.index.tree.metrical.covertree.SimplifiedCoverTree.CoverTreePrioritySearcher: Maximum distance of current node.
maxDist - Variable in class elki.index.tree.metrical.covertree.SimplifiedCoverTree.Node: Maximum distance to descendants.
maxDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.EuclideanDistance: Maximum distance of two objects.
maxDistance(DoubleDBIDList) - Method in class elki.index.tree.metrical.covertree.AbstractCoverTree: Find maximum in a list via scanning.
maxDistLevel(DBID, int) - Method in class elki.outlier.distance.HilOut.HilbertFeatures: maxDist function calculate the maximal Distance from Vector p to the border of the corresponding r-region at the given level
maxDistP - Variable in class elki.index.vafile.PartialVAFile.PartialVACandidate: (Current) maximum distance of this candidate.
maxdx - Variable in class elki.math.geometry.XYCurve: Drawing bounds for x
maxdy - Variable in class elki.math.geometry.XYCurve: Drawing bounds for y
maxEmIterations - Variable in class elki.clustering.subspace.P3C: Maximum number of iterations for the EM step.
maxEmIterations - Variable in class elki.clustering.subspace.P3C.Par: Maximum number of iterations for the EM step.
MaxExtensionBulkSplit - Class in elki.index.tree.spatial.rstarvariants.strategies.bulk: Split strategy for bulk-loading a spatial tree where the split axes are the dimensions with maximum extension.
MaxExtensionBulkSplit() - Constructor for class elki.index.tree.spatial.rstarvariants.strategies.bulk.MaxExtensionBulkSplit: Constructor
MaxExtensionBulkSplit.Par - Class in elki.index.tree.spatial.rstarvariants.strategies.bulk: Parameterization class.
MaxExtensionSortTileRecursiveBulkSplit - Class in elki.index.tree.spatial.rstarvariants.strategies.bulk: This is variation of the SortTileRecursiveBulkSplit, incorporating some ideas from MaxExtensionBulkSplit.
MaxExtensionSortTileRecursiveBulkSplit() - Constructor for class elki.index.tree.spatial.rstarvariants.strategies.bulk.MaxExtensionSortTileRecursiveBulkSplit
MaxExtensionSortTileRecursiveBulkSplit.Par - Class in elki.index.tree.spatial.rstarvariants.strategies.bulk: Parameterization class.
MAXFAST - Static variable in class elki.math.statistics.distribution.HaltonUniformDistribution: Maximum number of iterations of fast variant
maxheight - Variable in class elki.outlier.density.IsolationForest.ForestBuilder: Maximum height
maxi - Variable in class elki.math.statistics.distribution.HaltonUniformDistribution: Maximum integer to use
maxima - Variable in class elki.algorithm.statistics.HopkinsStatisticClusteringTendency: Stores the maximum in each dimension.
maxima - Variable in class elki.algorithm.statistics.HopkinsStatisticClusteringTendency.Par: Stores the maximum in each dimension.
maxima - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization: Stores the maximum in each dimension.
maxima - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization.Par: Stores the maximum in each dimension.
maxima - Variable in class elki.datasource.filter.transform.PerturbationFilter: Stores the maximum in each dimension.
maxima - Variable in class elki.datasource.filter.transform.PerturbationFilter.Par: Stores the maximum in each dimension.
MAXIMA_ID - Static variable in class elki.algorithm.statistics.HopkinsStatisticClusteringTendency.Par: Parameter for maximum.
MAXIMA_ID - Static variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization.Par: Parameter for maximum.
MAXIMA_ID - Static variable in class elki.datasource.filter.transform.PerturbationFilter.Par: Parameter for maximum.
maximum - Variable in class elki.clustering.optics.OPTICSXi.SteepArea: Maximum value
maximum(int) - Static method in class elki.evaluation.scores.DCGEvaluation: Maximum DCG.
MAXIMUM - elki.clustering.correlation.cash.ParameterizationFunction.ExtremumType: Maximum.
MaximumConditionalEntropy - Class in elki.math.statistics.dependence: Compute a mutual information based dependence measure using a nested means discretization, originally proposed for ordering axes in parallel coordinate plots.
MaximumConditionalEntropy() - Constructor for class elki.math.statistics.dependence.MaximumConditionalEntropy
MaximumConditionalEntropy.Par - Class in elki.math.statistics.dependence: Parameterization class.
MaximumDistance - Class in elki.distance.minkowski: Maximum distance for NumberVectors.
MaximumDistance() - Constructor for class elki.distance.minkowski.MaximumDistance: Deprecated.
Use static instance!
MaximumDistance.Par - Class in elki.distance.minkowski: Parameterization class.
MaximumF1Evaluation - Class in elki.evaluation.scores: Evaluate using the maximum F1 score.
MaximumF1Evaluation() - Constructor for class elki.evaluation.scores.MaximumF1Evaluation
MaximumF1Evaluation.Par - Class in elki.evaluation.scores: Parameterization class.
MaximumMatchingAccuracy - Class in elki.evaluation.clustering: Calculates the accuracy of a clustering based on the maximum set matching found by the Hungarian algorithm.
MaximumMatchingAccuracy(ClusterContingencyTable) - Constructor for class elki.evaluation.clustering.MaximumMatchingAccuracy: Calculate the maximum matching accuracy.
maxint - Variable in class elki.visualization.style.ClusterStylingPolicy: Intensity scaling
maxIntegerDigits(double[]) - Method in class elki.math.linearalgebra.LinearEquationSystem: Returns the maximum integer digits of the specified values.
maxIntegerDigits(double[][]) - Method in class elki.math.linearalgebra.LinearEquationSystem: Returns the maximum integer digits in each column of the specified values.
maxIntersection(Map<Integer, ModifiableDBIDs>, ModifiableDBIDs) - Method in class elki.clustering.subspace.DiSH.Instance: Returns the index of the set having the maximum intersection set with the specified set contained in the specified map.
MAXIT - Static variable in class elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator: Maximum number of iterations.
MAXIT - Static variable in class elki.math.statistics.distribution.estimator.WeibullLMMEstimator: Maximum number of iterations.
maxiter - Variable in class elki.clustering.affinitypropagation.AffinityPropagation: Maximum number of iterations.
maxiter - Variable in class elki.clustering.em.BetulaGMM: Maximum number of iterations.
maxiter - Variable in class elki.clustering.em.BetulaGMM.Par: Maximum number of iterations.
maxiter - Variable in class elki.clustering.em.EM: Maximum number of iterations to allow
maxiter - Variable in class elki.clustering.em.EM.Par: Maximum number of iterations.
maxiter - Variable in class elki.clustering.em.KDTreeEM: maximum amount of iterations
maxiter - Variable in class elki.clustering.em.KDTreeEM.Par: Maximum number of iterations.
maxiter - Variable in class elki.clustering.hierarchical.birch.BIRCHLloydKMeans: Maximum number of iterations.
maxiter - Variable in class elki.clustering.hierarchical.birch.BIRCHLloydKMeans.Par: Maximum number of iterations.
maxiter - Variable in class elki.clustering.kmeans.AbstractKMeans: Maximum number of iterations
maxiter - Variable in class elki.clustering.kmeans.AbstractKMeans.Par: Maximum number of iterations.
maxiter - Variable in class elki.clustering.kmeans.FuzzyCMeans: Maximum number of iterations to allow
maxiter - Variable in class elki.clustering.kmeans.FuzzyCMeans.Par: Maximum number of iterations.
maxiter - Variable in class elki.clustering.kmedoids.AlternatingKMedoids: Maximum number of iterations.
maxiter - Variable in class elki.clustering.kmedoids.AlternatingKMedoids.Par: The maximum number of iterations
maxiter - Variable in class elki.clustering.kmedoids.initialization.AlternateRefinement: Maximum number of refinement iterations.
maxiter - Variable in class elki.clustering.kmedoids.initialization.AlternateRefinement.Par: Maximum number of refinement iterations.
maxiter - Variable in class elki.clustering.kmedoids.PAM: The maximum number of iterations.
maxiter - Variable in class elki.clustering.kmedoids.PAM.Par: The maximum number of iterations.
maxiter - Variable in class elki.clustering.uncertain.UKMeans: Maximum number of iterations
maxiter - Variable in class elki.clustering.uncertain.UKMeans.Par: Maximum number of iterations
maxiter - Variable in class elki.outlier.clustering.EMOutlier: Maximum number of iterations to allow
maxiter - Variable in class elki.outlier.clustering.EMOutlier.Par: Maximum number of iterations.
maxiter - Variable in class tutorial.clustering.SameSizeKMeans.Par: Number of iterations.
MAXITER - Static variable in class elki.clustering.NaiveMeanShiftClustering: Maximum number of iterations.
MAXITER_ID - Static variable in class elki.clustering.em.EM.Par: Parameter to specify the maximum number of iterations.
MAXITER_ID - Static variable in class elki.clustering.em.KDTreeEM.Par: Parameter to specify a maximum number of iterations
MAXITER_ID - Static variable in interface elki.clustering.kmeans.KMeans: Parameter to specify the number of clusters to find, must be an integer greater or equal to 0, where 0 means no limit.
MAXITER_P - Static variable in class elki.clustering.kmedoids.initialization.AlternateRefinement.Par: Maximum number of refinement steps.
maxk - Variable in class elki.algorithm.statistics.EvaluateRetrievalPerformance: K nearest neighbors to use for classification evaluation.
maxk - Variable in class elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators: Benchmark parameters.
maxk - Variable in class elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Par: Benchmark parameters.
maxk - Variable in class elki.evaluation.outlier.OutlierPrecisionAtKCurve: Maximum value for k
maxk - Variable in class elki.evaluation.outlier.OutlierPrecisionAtKCurve.Par: Maximum value for k
MAXK_ID - Static variable in class elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Par: Final neighborhood size.
maxleaves - Variable in class elki.clustering.hierarchical.birch.CFTree.Factory: Maximum number of leaves (absolute or relative)
maxleaves - Variable in class elki.clustering.hierarchical.birch.CFTree.Factory.Par: Maximum number of leaves (absolute or relative)
maxleaves - Variable in class elki.index.tree.betula.CFTree.Factory: Maximum number of leaves (absolute or relative)
maxleaves - Variable in class elki.index.tree.betula.CFTree.Factory.Par: Maximum number of leaves (absolute or relative)
maxleaves - Variable in class elki.index.tree.betula.CFTree: Maximum number of leaves allowed
MAXLEAVES_ID - Static variable in class elki.clustering.hierarchical.birch.CFTree.Factory.Par: Maximum number of leaves.
MAXLEAVES_ID - Static variable in class elki.index.tree.betula.CFTree.Factory.Par: Maximum number of leaves.
maxlength - Variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm: Parameter for minimum and maximum length.
maxlength - Variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm.Par: Parameter for minimum and maximum length.
maxLength() - Method in class elki.itemsetmining.associationrules.AssociationRuleGeneration.ItemsetSearcher: Length of longest itemset.
MAXLENGTH_ID - Static variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm.Par: Parameter to specify the maximum itemset length.
maxLevel - Variable in class elki.clustering.correlation.CASH: Maximum level for splitting the hypercube.
maxLevel - Variable in class elki.clustering.correlation.CASH.Par: Maximum level for splitting the hypercube.
MAXLEVEL_ID - Static variable in class elki.clustering.correlation.CASH.Par: Parameter to specify the maximum level for splitting the hypercube, must be an integer greater than 0.
MAXLINEAR - elki.visualization.style.ClusterStylingPolicy.IntensityTransform
maxLMDim - Variable in class elki.clustering.correlation.LMCLUS: Maximum cluster dimensionality
maxmeasure - Variable in class elki.itemsetmining.associationrules.AssociationRuleGeneration: Parameter for maximum interestingness measure.
maxmeasure - Variable in class elki.itemsetmining.associationrules.AssociationRuleGeneration.Par: Parameter for maximum interestingness measure.
MAXMEASURE_ID - Static variable in class elki.itemsetmining.associationrules.AssociationRuleGeneration.Par: Parameter to specify the maximum threshold for the interestingness measure.
maxnc - Variable in class elki.index.laesa.LAESA.LAESAKNNSearcher: Maximum number of distance computations before also pruning reference points.
maxneighbor - Variable in class elki.clustering.kmedoids.CLARANS: Sampling rate.
maxneighbor - Variable in class elki.clustering.kmedoids.CLARANS.Par: Maximum neighbors to explore.
maxNMI() - Method in class elki.evaluation.clustering.Entropy: Get the max-normalized mutual information.
MAXQUADRATIC - elki.visualization.style.ClusterStylingPolicy.IntensityTransform
maxQuant - Variable in class elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier: Minimum and maximum number of samples.
maxQuant - Variable in class elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier.Par: Minimum and maximum number of samples.
maxRegLevel(int, int) - Method in class elki.outlier.distance.HilOut.HilbertFeatures: Level of the maximum region containing ref but not q
maxruns - Variable in class elki.math.linearalgebra.fitting.LevenbergMarquardtMethod: Maximum number of iterations in run()
maxsmall - Variable in class elki.math.linearalgebra.fitting.LevenbergMarquardtMethod: Maximum number of small improvements (stopping condition)
maxSorting - Variable in class elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split: The entries sorted according to their max values of their MBRs.
maxSplitDimension - Variable in class elki.clustering.correlation.cash.CASHInterval: Holds the maximum dimension which has already been split.
MAXTICKS - Static variable in class elki.math.scales.LinearScale: Maximum number of steps at which to decrease the resolution.
maxValues - Variable in class elki.math.spacefillingcurves.ZCurveTransformer: Maximum values in each dimension.
maxViolating(int[]) - Method in class elki.svm.solver.Solver
maxx - Variable in class elki.math.geometry.XYCurve: Minimum and maximum for X axis
maxx - Variable in class elki.math.geometry.XYPlot: Minimum and maximum for X axis
maxx - Variable in class elki.visualization.projections.CanvasSize: Maximum X
maxy - Variable in class elki.math.geometry.XYCurve: Minimum and maximum for Y axis
maxy - Variable in class elki.math.geometry.XYPlot: Minimum and maximum for Y axis
maxy - Variable in class elki.visualization.projections.CanvasSize: Maximum Y
mbr - Variable in class elki.index.tree.spatial.SpatialDirectoryEntry: The minimum bounding rectangle of the underlying spatial node.
mbr(DoubleIntPair[], int, int) - Method in class elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split: Computes and returns the mbr of the specified nodes, only the nodes between from and to index are considered.
mbw - Variable in class elki.clustering.em.KDTreeEM: minimum leaf size
mbw - Variable in class elki.clustering.em.KDTreeEM.Par: construction threshold
MBW_ID - Static variable in class elki.clustering.em.KDTreeEM.Par: Parameter to specify the termination criterion for kd-tree construction.
MCDEDependence - Class in elki.math.statistics.dependence: Implementation of bivariate Monte Carlo Density Estimation as described in
MCDEDependence(int, double, double, RandomFactory, MCDETest<?>) - Constructor for class elki.math.statistics.dependence.MCDEDependence: Constructor.
MCDEDependence.Par - Class in elki.math.statistics.dependence: Parameterizer
mcdeTest - Variable in class elki.math.statistics.dependence.MCDEDependence: Statistical Test returning p-value tailored to MCDE Framework.
mcdeTest - Variable in class elki.math.statistics.dependence.MCDEDependence.Par: Holds the value of MCDEDependence.Par.TEST_ID.
MCDETest<R extends MCDETest.RankStruct> - Interface in elki.math.statistics.dependence.mcde: Interface for statistical tests for MCDEDependence.
MCDETest.RankStruct - Class in elki.math.statistics.dependence.mcde: Structure to hold return values in index creation for MCDEDependence
mdist(double[], double[]) - Method in class elki.math.geometry.GrahamScanConvexHull2D: Manhattan distance.
mean - Variable in class elki.clustering.em.models.DiagonalGaussianModel: Mean vector.
mean - Variable in class elki.clustering.em.models.MultivariateGaussianModel: Mean vector.
mean - Variable in class elki.clustering.em.models.SphericalGaussianModel: Mean vector.
mean - Variable in class elki.clustering.em.models.TextbookMultivariateGaussianModel: Mean vector.
mean - Variable in class elki.clustering.em.models.TextbookSphericalGaussianModel: Mean vector.
mean - Variable in class elki.clustering.em.models.TwoPassMultivariateGaussianModel: Mean vector.
mean - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMeanNormalization: Stores the mean in each dimension.
mean - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization: Stores the mean in each dimension.
mean - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization.Par: Stores the mean in each dimension.
mean - Variable in class elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform: Vector for data set centering.
mean - Variable in class elki.index.preprocessed.knn.NaiveProjectedKNNPreprocessor: Mean number of distance computations.
mean - Variable in class elki.index.preprocessed.knn.SpacefillingKNNPreprocessor: Mean number of distance computations
mean - Variable in class elki.index.preprocessed.knn.SpacefillingMaterializeKNNPreprocessor: Mean number of distance computations
mean - Variable in class elki.index.tree.betula.features.VIIFeature: mean
mean - Variable in class elki.index.tree.betula.features.VVIFeature: mean
mean - Variable in class elki.index.tree.betula.features.VVVFeature: mean
mean - Variable in class elki.math.linearalgebra.CovarianceMatrix: The means.
mean - Variable in class elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution: Mean value for the generator
mean - Variable in class elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution.Par: Parameters.
mean - Variable in class elki.math.statistics.distribution.GumbelDistribution.Par: Parameters.
mean - Variable in class elki.math.statistics.distribution.InverseGaussianDistribution: Location value
mean - Variable in class elki.math.statistics.distribution.InverseGaussianDistribution.Par: Parameters.
mean - Variable in class elki.math.statistics.distribution.NormalDistribution: Mean value for the generator
mean - Variable in class elki.math.statistics.distribution.RayleighDistribution.Par: Parameters.
mean - Variable in class elki.math.statistics.distribution.SkewGeneralizedNormalDistribution.Par: Parameters
mean - Variable in class elki.utilities.scaling.outlier.HeDESNormalizationOutlierScaling: Mean
mean - Variable in class elki.utilities.scaling.outlier.SqrtStandardDeviationScaling: Effective parameters.
mean - Variable in class elki.utilities.scaling.outlier.SqrtStandardDeviationScaling.Par: Pre-fixed minimum and mean.
mean - Variable in class elki.utilities.scaling.outlier.StandardDeviationScaling: Mean to use
Mean - Class in elki.math: Compute the mean using a numerically stable online algorithm.
Mean() - Constructor for class elki.math.Mean: Empty constructor
Mean(Mean) - Constructor for class elki.math.Mean: Constructor from other instance
MEAN - elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Aggregate using the mean only.
MEAN - elki.index.tree.betula.CFTree.Threshold: Split halfway between minimum and maximum.
MEAN_ID - Static variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization.Par: Parameter for means.
MEAN_ID - Static variable in class elki.utilities.scaling.outlier.OutlierLinearScaling.Par: Flag to use the mean as minimum for scaling.
MEAN_ID - Static variable in class elki.utilities.scaling.outlier.SqrtStandardDeviationScaling.Par: Parameter to specify a fixed mean to use.
MEAN_ID - Static variable in class elki.utilities.scaling.outlier.StandardDeviationScaling.Par: Parameter to specify a fixed mean to use.
MEAN_STDDEV - elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Aggregate as mean and standard deviation.
MEAN_STDDEV_MIN_MAX - elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Aggregate as mean and standard deviation.
MeanModel - Class in elki.data.model: Cluster model that stores a mean for the cluster.
MeanModel(double[]) - Constructor for class elki.data.model.MeanModel: Constructor with mean
means - Variable in class elki.clustering.kmeans.AbstractKMeans.Instance: Cluster means.
means - Variable in class elki.clustering.kmeans.parallel.KMeansProcessor.Instance: Current mean vectors.
means - Variable in class elki.clustering.kmeans.parallel.KMeansProcessor: Mean vectors.
means(int[], double[][], ClusteringFeature[], int[]) - Method in class elki.clustering.hierarchical.birch.BIRCHLloydKMeans: Calculate means of clusters.
means(int[], double[][], ArrayList<? extends ClusterFeature>, int[]) - Method in class elki.clustering.kmeans.BetulaLloydKMeans: Calculate means of clusters.
means(List<? extends DBIDs>, double[][], Relation<? extends NumberVector>) - Static method in class elki.clustering.kmeans.AbstractKMeans: Returns the mean vectors of the given clusters in the given database.
means(List<? extends DBIDs>, double[][], Relation<? extends NumberVector>) - Static method in class elki.clustering.kmeans.spherical.SphericalKMeans.Instance: Returns the mean vectors of the given clusters in the given database.
means(List<? extends ModifiableDBIDs>, List<double[]>, Relation<DiscreteUncertainObject>) - Method in class elki.clustering.uncertain.UKMeans: Returns the mean vectors of the given clusters in the given database.
meansFromSums(double[][], double[][], double[][]) - Method in class elki.clustering.kmeans.AbstractKMeans.Instance: Compute means from cluster sums by averaging.
meansFromSums(double[][], double[][], double[][]) - Method in class elki.clustering.kmeans.spherical.SphericalKMeans.Instance: Compute means from cluster sums by adding and normalizing.
meansWithTreshhold(double) - Method in class elki.clustering.kmeans.KMeansMinusMinus.Instance: Returns the mean vectors of the given clusters in the given database.
MeanVariance - Class in elki.math: Do some simple statistics (mean, variance) using a numerically stable online algorithm.
MeanVariance() - Constructor for class elki.math.MeanVariance: Empty constructor
MeanVariance(MeanVariance) - Constructor for class elki.math.MeanVariance: Constructor from other instance
MeanVarianceDistributionEstimator<D extends Distribution> - Interface in elki.math.statistics.distribution.estimator: Interface for estimators that only need mean and variance.
MeanVarianceMinMax - Class in elki.math: Class collecting mean, variance, minimum and maximum statistics.
MeanVarianceMinMax() - Constructor for class elki.math.MeanVarianceMinMax: Constructor.
MeanVarianceMinMax(MeanVarianceMinMax) - Constructor for class elki.math.MeanVarianceMinMax: Constructor cloning existing statistics.
MeanVarianceSplit - Class in elki.index.tree.spatial.kd.split: Split on the median of the axis with the largest variance.
MeanVarianceSplit() - Constructor for class elki.index.tree.spatial.kd.split.MeanVarianceSplit
MeanVarianceSplit.Par - Class in elki.index.tree.spatial.kd.split: Parameterizer
MEANVISITOR - Variable in class elki.clustering.biclustering.ChengAndChurch.BiclusterCandidate: Visitor for updating the means.
measure - Variable in class elki.itemsetmining.associationrules.AssociationRule: Measure of the Rule.
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.AddedValue
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.CertaintyFactor
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.Confidence
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.Conviction
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.Cosine
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.GiniIndex
measure(int, int, int, int) - Method in interface elki.itemsetmining.associationrules.interest.InterestingnessMeasure: Computes the value of the measure for a given support values
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.Jaccard
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.JMeasure
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.Klosgen
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.LaplaceCorrectedConfidence
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.Leverage
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.Lift
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.OddsRatio
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.PhiCorrelationCoefficient
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.SebagSchonauer
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.YulesQ
measure(int, int, int, int) - Method in class elki.itemsetmining.associationrules.interest.YulesY
Measurement(String, double, double, double, boolean) - Constructor for class elki.result.EvaluationResult.Measurement: Constructor.
Measurement(String, double, double, double, double, boolean) - Constructor for class elki.result.EvaluationResult.Measurement: Constructor.
MeasurementGroup(String) - Constructor for class elki.result.EvaluationResult.MeasurementGroup: Constructor.
measurements - Variable in class elki.result.EvaluationResult.MeasurementGroup: Measurements in this group.
MED_MAD - elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Aggregate using median and MAD.
MED_MAD_MIN_MAX - elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Aggregate using median and MAD.
median - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMADNormalization: Stores the median in each dimension.
median(double[]) - Static method in class elki.utilities.datastructures.QuickSelect: Compute the median of an array efficiently using the QuickSelect method.
median(double[], int, int) - Static method in class elki.utilities.datastructures.QuickSelect: Compute the median of an array efficiently using the QuickSelect method.
median(ArrayModifiableDBIDs, Comparator<? super DBIDRef>) - Static method in class elki.database.ids.QuickSelectDBIDs: Compute the median of an array efficiently using the QuickSelect method.
median(ArrayModifiableDBIDs, Comparator<? super DBIDRef>, int, int) - Static method in class elki.database.ids.QuickSelectDBIDs: Compute the median of an array efficiently using the QuickSelect method.
median(ModifiableDoubleDBIDList) - Static method in class elki.database.ids.QuickSelectDBIDs: Compute the median of an array efficiently using the QuickSelect method.
median(ModifiableDoubleDBIDList, int, int) - Static method in class elki.database.ids.QuickSelectDBIDs: Compute the median of an array efficiently using the QuickSelect method.
median(List<? extends T>, Comparator<? super T>) - Static method in class elki.utilities.datastructures.QuickSelect: Compute the median of an array efficiently using the QuickSelect method.
median(List<? extends T>, Comparator<? super T>, int, int) - Static method in class elki.utilities.datastructures.QuickSelect: Compute the median of an array efficiently using the QuickSelect method.
MEDIAN - elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Aggregate using median.
MEDIAN - elki.clustering.kmeans.KDTreePruningKMeans.Split: K-d-tree typical median split that guarantees minimal height, but tends to produce larger cells.
MEDIAN - elki.index.tree.betula.CFTree.Threshold: Split using the median.
MEDIAN - tutorial.clustering.NaiveAgglomerativeHierarchicalClustering3.Linkage
MEDIAN - tutorial.clustering.NaiveAgglomerativeHierarchicalClustering4.Linkage
MedianLinkage - Class in elki.clustering.hierarchical.linkage: Median-linkage — weighted pair group method using centroids (WPGMC).
MedianLinkage() - Constructor for class elki.clustering.hierarchical.linkage.MedianLinkage: Deprecated.
use the static instance MedianLinkage.STATIC instead.
MedianLinkage.Par - Class in elki.clustering.hierarchical.linkage: Class parameterizer.
medians(List<? extends DBIDs>, double[][], Relation<? extends NumberVector>) - Method in class elki.clustering.kmeans.KMediansLloyd.Instance: Returns the median vectors of the given clusters in the given database.
MedianSplit - Class in elki.index.tree.spatial.kd.split: Split on the median of the axis with the largest length.
MedianSplit() - Constructor for class elki.index.tree.spatial.kd.split.MedianSplit
MedianSplit.Par - Class in elki.index.tree.spatial.kd.split: Parameterizer
MedianVarianceSplit - Class in elki.index.tree.spatial.kd.split: Split on the median of the axis with the largest variance.
MedianVarianceSplit() - Constructor for class elki.index.tree.spatial.kd.split.MedianVarianceSplit
MedianVarianceSplit.Par - Class in elki.index.tree.spatial.kd.split: Parameterizer
MedoidLinkage<O> - Class in elki.clustering.hierarchical: Medoid linkage uses the distance of medoids as criterion.
MedoidLinkage(Distance<? super O>) - Constructor for class elki.clustering.hierarchical.MedoidLinkage: Constructor.
MedoidLinkage.Instance - Class in elki.clustering.hierarchical: Main worker instance of AGNES.
MedoidModel - Class in elki.data.model: Cluster model that stores a mean for the cluster.
MedoidModel(DBID) - Constructor for class elki.data.model.MedoidModel: Constructor with medoid
medoids - Variable in class elki.clustering.kmedoids.CLARANS.Assignment: Medoids
medoidsilhouette(IntegerDataStore, DBIDArrayIter) - Method in class elki.clustering.silhouette.PAMMEDSIL.Instance: Evaluate the average medoid Silhouette of the current cluster assignment
medoidsilhouette(IntegerDataStore, DBIDArrayIter, int, DBIDRef) - Method in class elki.clustering.silhouette.PAMMEDSIL.Instance: Evaluate the average medoid Silhouette of the current cluster assignment
MedoidsInstance(DBIDs, DistanceQuery<?>, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.KMeansPlusPlus.MedoidsInstance
MEGA - Static variable in class elki.database.query.EmpiricalQueryOptimizer: Megabytes for formatting memory.
MEGABYTES - Static variable in class elki.svm.qmatrix.CachedQMatrix: Constant for parameterization in megabytes
members - Variable in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster: New ids, not yet in child clusters.
MemoryDataStoreFactory - Class in elki.database.datastore.memory: Simple factory class that will store all data in memory using object arrays or hashmaps.
MemoryDataStoreFactory() - Constructor for class elki.database.datastore.memory.MemoryDataStoreFactory
MemoryKDTree<O extends NumberVector> - Class in elki.index.tree.spatial.kd: Implementation of a static in-memory K-D-tree.
MemoryKDTree(Relation<O>, int) - Constructor for class elki.index.tree.spatial.kd.MemoryKDTree: Constructor with default split (used by EmpiricalQueryOptimizer).
MemoryKDTree(Relation<O>, SplitStrategy, int) - Constructor for class elki.index.tree.spatial.kd.MemoryKDTree: Constructor.
MemoryKDTree.CountingRelation - Class in elki.index.tree.spatial.kd: Proxy to count accesses.
MemoryKDTree.Factory<O extends NumberVector> - Class in elki.index.tree.spatial.kd: Factory class
MemoryKDTree.Factory.Par<O extends NumberVector> - Class in elki.index.tree.spatial.kd: Parameterization class.
MemoryKDTree.KDNode - Class in elki.index.tree.spatial.kd: KD tree node.
MemoryKDTree.KDTreeKNNSearcher - Class in elki.index.tree.spatial.kd: kNN query for the k-d-tree.
MemoryKDTree.KDTreePrioritySearcher - Class in elki.index.tree.spatial.kd: Priority search for the k-d-tree.
MemoryKDTree.KDTreeRangeSearcher - Class in elki.index.tree.spatial.kd: Range query for the k-d-tree.
MemoryKDTree.PrioritySearchBranch - Class in elki.index.tree.spatial.kd: Search position for priority search.
MemoryPageFile<P extends Page> - Class in elki.persistent: A memory based implementation of a PageFile that simulates I/O-access.
MemoryPageFile(int) - Constructor for class elki.persistent.MemoryPageFile: Creates a new MemoryPageFile that is supported by a cache with the specified parameters.
MemoryPageFileFactory<P extends Page> - Class in elki.persistent: Page file factory for memory page files.
MemoryPageFileFactory(int) - Constructor for class elki.persistent.MemoryPageFileFactory: Constructor.
MemoryPageFileFactory.Par - Class in elki.persistent: Parameterization class.
MENU - elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Instance.State
menubar - Variable in class elki.visualization.gui.ResultWindow.DynamicMenu: Menubar component
menubar - Variable in class elki.visualization.gui.ResultWindow
menuItemClicked(int) - Method in class elki.visualization.parallel3d.util.SimpleMenuOverlay: Callback when a menu item was clicked.
menuOverlay - Variable in class elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Instance: Menu overlay.
menuStarter - Variable in class elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Instance: Handler to open the menu.
merge(double[], int, double[], int) - Method in class elki.clustering.hierarchical.linkage.CentroidLinkage
merge(double[], int, double[], int) - Method in interface elki.clustering.hierarchical.linkage.GeometricLinkage: Merge the aggregated vectors.
merge(double[], int, double[], int) - Method in class elki.clustering.hierarchical.linkage.MedianLinkage
merge(double[], int, double[], int) - Method in class elki.clustering.hierarchical.linkage.WardLinkage
merge(double, int, int) - Method in class elki.clustering.hierarchical.AGNES.Instance: Execute the cluster merge.
merge(double, int, int) - Method in class elki.clustering.hierarchical.Anderberg.Instance
merge(int, double[][], ClusterMergeHistoryBuilder, int[], double, int, int) - Method in class elki.clustering.hierarchical.LinearMemoryNNChain.Instance: Execute the cluster merge.
merge(int, int) - Method in class elki.clustering.hierarchical.HACAM.Instance: Execute the cluster merge.
merge(int, int) - Method in class elki.clustering.hierarchical.MedoidLinkage.Instance: Execute the cluster merge.
merge(int, int) - Method in class elki.clustering.hierarchical.MiniMax.Instance: Merges two clusters given by x, y, their points with smallest IDs, and y to keep
merge(int, int) - Method in class elki.clustering.hierarchical.MiniMaxAnderberg.Instance
merge(Relation<? extends NumberVector>, List<ORCLUS.ORCLUSCluster>, int, int, IndefiniteProgress) - Method in class elki.clustering.correlation.ORCLUS: Reduces the number of seeds to k_new
merge(DoubleMinMax) - Method in class elki.parallel.processor.DoubleMinMaxProcessor: Merge the result of an instance.
MERGE_NOISE - elki.evaluation.clustering.internal.NoiseHandling: Merge all noise into a cluster
mergeClusterCores(int, ArrayList<P3C.Signature>) - Method in class elki.clustering.subspace.P3C: Merge 1-signatures into p-signatures.
mergeClusterInformation(ModifiableDBIDs, WritableIntegerDataStore, WritableDataStore<Assignment>) - Method in class elki.clustering.dbscan.GriDBSCAN.Instance: Merge cluster information.
mergecount - Variable in class elki.clustering.hierarchical.ClusterMergeHistoryBuilder: Merge counter (for merge ordering).
mergeCSSFrom(CSSClassManager) - Method in class elki.visualization.css.CSSClassManager: Merge CSS classes, for example to merge two plots.
mergeDistance - Variable in class elki.clustering.hierarchical.ClusterMergeHistoryBuilder: Distance to the parent object.
MergedParameterization - Class in elki.utilities.optionhandling.parameterization: This configuration can be "rewound" to allow the same values to be consumed multiple times, by different classes.
MergedParameterization(Parameterization) - Constructor for class elki.utilities.optionhandling.parameterization.MergedParameterization: Constructor.
MergedParameterization(Parameterization, ListParameterization, List<ListParameterization.ParameterPair>) - Constructor for class elki.utilities.optionhandling.parameterization.MergedParameterization: Constructor for descending
mergeJoin(DBIDs, DBIDs) - Method in class elki.itemsetmining.Eclat
merges - Variable in class elki.clustering.hierarchical.ClusterMergeHistory: Store merge order (two cluster references per merge).
merges - Variable in class elki.clustering.hierarchical.ClusterMergeHistoryBuilder: Store merge order.
merges - Variable in class elki.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance: The hierarchical result to process.
merges - Variable in class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Instance: The hierarchical result to process.
merges - Variable in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Instance: The hierarchical result to process.
merges - Variable in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Instance: The hierarchical result to process.
mergeSignatures(P3C.Signature, P3C.Signature, int) - Method in class elki.clustering.subspace.P3C: Generates a merged signature of this and another one, where the other signature must be a 1-signature.
mergeWith(Core) - Method in class elki.clustering.dbscan.util.Core: Merge two cores.
message - Variable in class elki.visualization.parallel3d.util.SimpleMessageOverlay: Message to display.
message(String) - Static method in class elki.logging.LoggingUtil: Static version to log a 'info' message.
message(String, Throwable) - Static method in class elki.logging.LoggingUtil: Static version to log a 'info' message.
MessageFormatter - Class in elki.logging: A formatter to simply retrieve the message of an LogRecord without printing origin information.
MessageFormatter() - Constructor for class elki.logging.MessageFormatter: Constructor.
messageOverlay - Variable in class elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Instance: Message overlay.
meta - Variable in class elki.datasource.bundle.BundleReader: Bundle metadata.
meta - Variable in class elki.datasource.bundle.MultipleObjectsBundle: Storing the meta data.
meta - Variable in class elki.datasource.bundle.SingleObjectBundle: Store the meta data.
meta - Variable in class elki.datasource.filter.AbstractStreamConversionFilter: The filtered meta.
meta - Variable in class elki.datasource.filter.cleaning.VectorDimensionalityFilter: The filtered meta.
meta - Variable in class elki.datasource.filter.FixedDBIDsFilter: The filtered meta
meta - Variable in class elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter: Current meta data
meta - Variable in class elki.datasource.parser.ClusteringVectorParser: Metadata.
meta - Variable in class elki.datasource.parser.NumberVectorLabelParser: Metadata.
meta - Variable in class elki.datasource.parser.SimplePolygonParser: Metadata.
meta - Variable in class elki.datasource.parser.SimpleTransactionParser: Metadata.
meta - Variable in class elki.itemsetmining.associationrules.AssociationRuleGeneration.Instance: Metadata for printing.
meta - Variable in class elki.result.AssociationRuleResult: Metadata of the data relation, for item labels.
meta - Variable in class elki.result.FrequentItemsetsResult: Metadata of the data relation, for item labels.
meta - Variable in class elki.result.outlier.OutlierResult: Outlier score meta information
meta - Variable in class elki.utilities.scaling.outlier.OutlierGammaScaling: Keep a reference to the outlier score meta, for normalization.
meta() - Method in class elki.datasource.bundle.MultipleObjectsBundle
meta() - Method in interface elki.datasource.bundle.ObjectBundle: Access the meta data.
meta() - Method in class elki.datasource.bundle.SingleObjectBundle
meta(int) - Method in class elki.datasource.bundle.MultipleObjectsBundle
meta(int) - Method in interface elki.datasource.bundle.ObjectBundle: Access the meta data.
meta(int) - Method in class elki.datasource.bundle.SingleObjectBundle
Meta(int) - Constructor for class tutorial.clustering.SameSizeKMeans.Meta: Constructor.
META_ALGORITHM_ID - Static variable in class elki.clustering.uncertain.RepresentativeUncertainClustering.Par: Parameter to hand an algorithm for creating the meta-clustering to our instance of RepresentativeUncertainClustering.
META_CHANGED - elki.datasource.bundle.BundleStreamSource.Event
metaAlgorithm - Variable in class elki.clustering.uncertain.RepresentativeUncertainClustering: The algorithm for meta-clustering.
metaAlgorithm - Variable in class elki.clustering.uncertain.RepresentativeUncertainClustering.Par: Field to store the inner algorithm for meta-clustering
Metadata - Class in elki.result: Metadata management class.
Metadata(Object) - Constructor for class elki.result.Metadata: Constructor, use via static methods only!
Metadata.CleanerThread - Class in elki.result: Cleanup thread.
Metadata.EagerIt<O> - Class in elki.result: Base class for iterators that need to look ahead, e.g., to check conditions on the next element.
Metadata.Hierarchy - Class in elki.result: Class to represent hierarchy information.
Metadata.Hierarchy.ItrAnc - Class in elki.result: Iterator over all ancestors.
Metadata.Hierarchy.ItrChildren - Class in elki.result: Child iterator.
Metadata.Hierarchy.ItrChildrenReverse - Class in elki.result: Child iterator.
Metadata.Hierarchy.ItrDesc - Class in elki.result: Iterator over all descendants.
Metadata.Hierarchy.ItrParents - Class in elki.result: Parent iterator.
Metadata.Hierarchy.ItrParentsReverse - Class in elki.result: Parent iterator.
metaLength() - Method in class elki.datasource.bundle.MultipleObjectsBundle
metaLength() - Method in interface elki.datasource.bundle.ObjectBundle: Get the metadata length.
metaLength() - Method in class elki.datasource.bundle.SingleObjectBundle
MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends Node<E>,E extends MTreeEntry> - Class in elki.index.preprocessed.knn: A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
MetricalIndexApproximationMaterializeKNNPreprocessor(Relation<O>, Distance<? super O>, int) - Constructor for class elki.index.preprocessed.knn.MetricalIndexApproximationMaterializeKNNPreprocessor: Constructor
MetricalIndexApproximationMaterializeKNNPreprocessor.Factory<O extends NumberVector,N extends Node<E>,E extends MTreeEntry> - Class in elki.index.preprocessed.knn: The parameterizable factory.
MetricalIndexApproximationMaterializeKNNPreprocessor.Factory.Par<O extends NumberVector,N extends Node<E>,E extends MTreeEntry> - Class in elki.index.preprocessed.knn: Parameterization class.
MetricalIndexTree<O,N extends Node<E>,E> - Class in elki.index.tree.metrical: Abstract super class for all metrical index classes.
MetricalIndexTree(PageFile<N>) - Constructor for class elki.index.tree.metrical.MetricalIndexTree: Constructor.
mfactory - Variable in class elki.clustering.em.EM: Factory for producing the initial cluster model.
mfactory - Variable in class elki.clustering.em.EM.Par: Cluster model factory.
mfactory - Variable in class elki.clustering.em.KDTreeEM: Factory for producing the initial cluster model.
mfactory - Variable in class elki.clustering.em.KDTreeEM.Par: Cluster model factory.
mfactory - Variable in class elki.outlier.clustering.EMOutlier: Factory for producing the initial cluster model.
mfactory - Variable in class elki.outlier.clustering.EMOutlier.Par: Cluster model factory.
mgamma - Variable in class elki.similarity.kernel.LaplaceKernel: Scaling factor mgamma. (= - 1/sigma)
mgamma - Variable in class elki.similarity.kernel.RadialBasisFunctionKernel: Scaling factor mgamma = -1/(2 sigma^2).
mi - Variable in class elki.clustering.hierarchical.MedoidLinkage.Instance: Iterators into medoid array.
mib - Variable in class elki.clustering.optics.OPTICSXi.SteepDownArea: Maximum in-between value (updated in OPTICSXi.updateFilterSDASet(double, java.util.List<elki.clustering.optics.OPTICSXi.SteepDownArea>, double)).
mid - Variable in class elki.clustering.kmeans.KDTreePruningKMeans.KDNode: Midpoint
midpoint - Variable in class elki.clustering.em.KDTreeEM.KDTree: Middle point of bounding box
MIDPOINT - elki.clustering.kmeans.KDTreePruningKMeans.Split: Split halfway between minimum and maximum.
MidpointSplit - Class in elki.index.tree.spatial.kd.split: Classic midpoint split, halfway on the axis of largest extend.
MidpointSplit() - Constructor for class elki.index.tree.spatial.kd.split.MidpointSplit
MidpointSplit.Par - Class in elki.index.tree.spatial.kd.split: Parameterizer
MillisTimeDuration - Class in elki.logging.statistics: Class that tracks the runtime of a task with System.nanoTime()
MillisTimeDuration(String) - Constructor for class elki.logging.statistics.MillisTimeDuration: Constructor.
min - Variable in class elki.data.HyperBoundingBox: The coordinates of the 'lower left' (= minimum) hyper point.
min - Variable in class elki.data.spatial.Polygon: Minimum values
min - Variable in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization: Minimum and maximum values.
min - Variable in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization.Par: Minimum and maximum values.
min - Variable in class elki.distance.external.FileBasedSparseDoubleDistance: Minimum and maximum IDs seen.
min - Variable in class elki.distance.external.FileBasedSparseFloatDistance: Minimum and maximum IDs seen.
min - Variable in class elki.math.DoubleMinMax: Minimum and maximum.
min - Variable in class elki.math.IntegerMinMax: Minimum and maximum.
min - Variable in class elki.math.linearalgebra.ConstrainedQuadraticProblemSolver.ProblemData
min - Variable in class elki.math.MeanVarianceMinMax: Minimum value
min - Variable in class elki.math.scales.LinearScale: min value of the scale
min - Variable in class elki.math.statistics.distribution.HaltonUniformDistribution: Minimum
min - Variable in class elki.math.statistics.distribution.HaltonUniformDistribution.Par: Parameters.
min - Variable in class elki.math.statistics.distribution.UniformDistribution: Minimum
min - Variable in class elki.math.statistics.distribution.UniformDistribution.Par: Parameters.
min - Variable in class elki.outlier.density.IsolationForest.ForestBuilder: Current value range
min - Variable in class elki.outlier.distance.HilOut.HilbertFeatures: Data space minimums
min - Variable in class elki.outlier.lof.ALOCI.ALOCIQuadTree: Tree parameters
min - Variable in class elki.result.EvaluationResult.Measurement: Observed value, minimum, maximum, expected value.
min - Variable in class elki.utilities.datastructures.range.CombinedIntGenerator: Minimum.
min - Variable in class elki.utilities.datastructures.range.StaticIntGenerator: Minimum.
min - Variable in class elki.utilities.scaling.ClipScaling: Field storing the minimum to use
min - Variable in class elki.utilities.scaling.ClipScaling.Par
min - Variable in class elki.utilities.scaling.outlier.OutlierLinearScaling: Field storing the Minimum to use
min - Variable in class elki.utilities.scaling.outlier.OutlierLinearScaling.Par: Field storing the Minimum to use
min - Variable in class elki.utilities.scaling.outlier.OutlierSqrtScaling: Minimum and maximum values.
min - Variable in class elki.utilities.scaling.outlier.OutlierSqrtScaling.Par: Predefined minimum value.
min - Variable in class elki.utilities.scaling.outlier.SqrtStandardDeviationScaling: Effective parameters.
min - Variable in class elki.utilities.scaling.outlier.SqrtStandardDeviationScaling.Par: Pre-fixed minimum and mean.
min - Variable in class elki.visualization.svg.SVGScoreBar: Value, minimum and maximum values
min(double, double) - Static method in class elki.math.MathUtil: Binary min, without handling of special values.
min(double, double, double) - Static method in class elki.math.MathUtil: Ternary min, without handling of special values.
min(double, double, double, double) - Static method in class elki.math.MathUtil: Quadrary min, without handling of special values.
min(int, int) - Static method in class elki.math.MathUtil: Binary min, without handling of special values.
min(int, int, int) - Static method in class elki.distance.strings.LevenshteinDistance: Three-way integer minimum.
min(int, int, int) - Static method in class elki.math.MathUtil: Ternary min, without handling of special values.
min(int, int, int, int) - Static method in class elki.math.MathUtil: Quadrary min, without handling of special values.
min(A, NumberArrayAdapter<?, A>, double, double) - Static method in interface elki.math.statistics.distribution.estimator.LogMOMDistributionEstimator: Utility function to find minimum and maximum values.
MIN_CLUSTER_SIZE_ID - Static variable in class elki.clustering.subspace.P3C.Par: Minimum cluster size for noise flagging.
MIN_COLUMN_REMOVE_THRESHOLD - Static variable in class elki.clustering.biclustering.ChengAndChurch: The minimum number of columns that the database must have so that a removal of columns is performed in ChengAndChurch.multipleNodeDeletion(double[][], elki.clustering.biclustering.ChengAndChurch.BiclusterCandidate).
MIN_GAIN - Static variable in class elki.projection.SNE: Minimum gain in learning rate.
MIN_GAIN - Static variable in class elki.projection.TSNE: Minimum gain in learning rate.
MIN_HEIGHT - Static variable in class elki.visualization.opticsplot.OPTICSPlot: Minimum and maximum vertical resolution.
MIN_HEIGHT - Static variable in class elki.visualization.silhouette.SilhouettePlot: Minimum and maximum vertical resolution.
MIN_ID - Static variable in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization.Par: Option ID for minimum value.
MIN_ID - Static variable in class elki.math.statistics.distribution.UniformDistribution.Par: Minimum value
MIN_ID - Static variable in class elki.utilities.scaling.ClipScaling: Parameter to specify a fixed minimum to use.
MIN_ID - Static variable in class elki.utilities.scaling.outlier.OutlierLinearScaling.Par: Parameter to specify a fixed minimum to use.
MIN_ID - Static variable in class elki.utilities.scaling.outlier.OutlierSqrtScaling.Par: Parameter to specify the fixed minimum to use.
MIN_ID - Static variable in class elki.utilities.scaling.outlier.SqrtStandardDeviationScaling.Par: Parameter to specify the fixed minimum to use.
MIN_LOGLIKELIHOOD - Static variable in class elki.clustering.em.BetulaGMM: Minimum loglikelihood to avoid -infinity.
MIN_LOGLIKELIHOOD - Static variable in class elki.clustering.em.EM: Minimum loglikelihood to avoid -infinity.
MIN_LOGLIKELIHOOD - Static variable in class elki.outlier.clustering.EMOutlier: Minimum loglikelihood to avoid -infinity.
MIN_PIJ - Static variable in class elki.projection.GaussianAffinityMatrixBuilder: Minimum value for pij entries (even when duplicate)
MIN_PIJ - Static variable in class elki.projection.PerplexityAffinityMatrixBuilder: Minimum value for pij entries (even when duplicate)
MIN_QIJ - Static variable in class elki.projection.SNE: Minimum value for qij entries (even when duplicate)
MIN_QIJ - Static variable in class elki.projection.TSNE: Minimum value for qij entries (even when duplicate)
MIN_ROW_REMOVE_THRESHOLD - Static variable in class elki.clustering.biclustering.ChengAndChurch: The minimum number of rows that the database must have so that a removal of rows is performed in ChengAndChurch.multipleNodeDeletion(double[][], elki.clustering.biclustering.ChengAndChurch.BiclusterCandidate).
minBandwidth - Variable in class elki.outlier.lof.KDEOS: Kernel minimum bandwidth.
minc - Variable in class elki.utilities.datastructures.KuhnMunkres: Position of uncovered minimum column
minClSize - Variable in class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction: Minimum cluster size.
minClSize - Variable in class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Par: Minimum cluster size.
minClSize - Variable in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction: Minimum cluster size.
minClSize - Variable in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Par: Minimum cluster size.
minClSize - Variable in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction: Minimum cluster size.
minClSize - Variable in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Par: Minimum cluster size.
minclusters - Variable in class elki.clustering.hierarchical.extraction.CutDendrogramByNumberOfClusters: Minimum number of clusters to extract
minclusters - Variable in class elki.clustering.hierarchical.extraction.CutDendrogramByNumberOfClusters.Par: Number of clusters to extract.
MINCLUSTERS_ID - Static variable in class elki.clustering.hierarchical.extraction.CutDendrogramByNumberOfClusters.Par: The minimum number of clusters to extract.
minClusterSize - Variable in class elki.clustering.subspace.P3C: Minimum cluster size for noise flagging.
minClusterSize - Variable in class elki.clustering.subspace.P3C.Par: Minimum cluster size for noise flagging.
MINCLUSTERSIZE_ID - Static variable in class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Par: The minimum size of clusters to extract.
MINCLUSTERSIZE_ID - Static variable in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Par: The minimum size of clusters to extract.
MINCLUSTERSIZE_ID - Static variable in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Par: The minimum size of clusters to extract.
minConfidence - Variable in class elki.timeseries.OfflineChangePointDetectionAlgorithm: Mininum confidence.
minConfidence - Variable in class elki.timeseries.OfflineChangePointDetectionAlgorithm.Par: Mininum confidence.
minCosAngle(SpatialComparable, SpatialComparable) - Static method in class elki.data.VectorUtil: Compute the minimum angle between two rectangles.
minDev - Variable in class elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier: Minimum and maximum allowed deviation.
minDev - Variable in class elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier.Par: Minimum and maximum allowed deviation.
minDev - Variable in class elki.data.uncertain.uncertainifier.UniformUncertainifier: Minimum and maximum allowed deviation.
minDev - Variable in class elki.data.uncertain.uncertainifier.UniformUncertainifier.Par: Minimum and maximum allowed deviation.
mindim - Variable in class elki.clustering.subspace.SUBCLU: Minimum dimensionality.
mindim - Variable in class elki.clustering.subspace.SUBCLU.Par: Minimum dimensionality.
mindim - Variable in class elki.data.projection.FeatureSelection: Minimum dimensionality required for projection.
mindim - Variable in class elki.data.projection.NumericalFeatureSelection: Minimum dimensionality required for projection.
mindim - Variable in class elki.data.type.VectorTypeInformation: Minimum dimensionality.
mindim - Variable in class elki.datasource.parser.NumberVectorLabelParser: Dimensionality reported.
mindim() - Method in class elki.data.type.VectorTypeInformation: Get the minimum dimensionality of the occurring vectors.
minDim - Variable in class elki.clustering.correlation.CASH: Minimum dimensionality of the subspaces to be found
minDim - Variable in class elki.clustering.correlation.CASH.Par: Minimum dimensionality of the subspaces to be found
MINDIM_ID - Static variable in class elki.clustering.correlation.CASH.Par: Parameter to specify the minimum dimensionality of the subspaces to be found, must be an integer greater than 0.
MINDIM_ID - Static variable in class elki.clustering.subspace.SUBCLU.Par: Minimum dimensionality to generate clusters.
mindist - Variable in class elki.algorithm.KNNJoin.Task: Minimum distance.
mindist - Variable in class elki.index.tree.metrical.mtreevariants.query.MTreeSearchCandidate: Distance value
mindist - Variable in class elki.index.tree.metrical.vptree.GNAT.PrioritySearchBranch: Minimum distance
mindist - Variable in class elki.index.tree.spatial.kd.MinimalisticMemoryKDTree.PrioritySearchBranch: Minimum distance
mindist - Variable in class elki.index.tree.spatial.kd.SmallMemoryKDTree.PrioritySearchBranch: Minimum distance
mindist - Variable in class elki.index.tree.spatial.rstarvariants.query.EuclideanRStarTreeDistancePrioritySearcher: Distance to current node
mindist - Variable in class elki.index.tree.spatial.rstarvariants.query.RStarTreeDistancePrioritySearcher: Distance to current node
mindist(double[], double[], double[]) - Method in class elki.clustering.kmeans.KDTreePruningKMeans.Instance: Get the smallest maximum distance for pruning.
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.ArcCosineDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.ArcCosineUnitlengthDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.BrayCurtisDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.CanberraDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.ClarkDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.colorhistogram.HistogramIntersectionDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.CosineDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.CosineUnitlengthDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.geo.DimensionSelectingLatLngDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.geo.LatLngDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.geo.LngLatDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.histogram.HistogramMatchDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.EuclideanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.LPIntegerNormDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.LPNormDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.ManhattanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.MaximumDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.MinimumDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.SquaredEuclideanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.WeightedEuclideanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.WeightedLPNormDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.WeightedManhattanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.WeightedMaximumDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.minkowski.WeightedSquaredEuclideanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.ChiDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.ChiSquaredDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.FisherRaoDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.HellingerDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.JeffreyDivergenceDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.JensenShannonDivergenceDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.SqrtJensenShannonDivergenceDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.TriangularDiscriminationDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.probabilistic.TriangularDistance
minDist(SpatialComparable, SpatialComparable) - Method in interface elki.distance.SpatialPrimitiveDistance: Computes the distance between the two given MBRs according to this distance function.
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.SqrtCosineDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.SqrtCosineUnitlengthDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.subspace.OnedimensionalDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.subspace.SubspaceEuclideanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.subspace.SubspaceLPNormDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.subspace.SubspaceManhattanDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.subspace.SubspaceMaximumDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.distance.WeightedCanberraDistance
minDist(SpatialComparable, SpatialComparable) - Method in class elki.similarity.Kulczynski1Similarity
minDist(SpatialComparable, DBIDRef) - Method in interface elki.database.query.distance.SpatialDistanceQuery: Computes the minimum distance between the given MBR and the FeatureVector object according to this distance function.
minDist(SpatialComparable, DBIDRef) - Method in class elki.database.query.distance.SpatialPrimitiveDistanceQuery
minDist(SpatialComparable, V) - Method in interface elki.database.query.distance.SpatialDistanceQuery: Computes the minimum distance between the given MBR and the FeatureVector object according to this distance function.
minDist(SpatialComparable, V) - Method in class elki.database.query.distance.SpatialPrimitiveDistanceQuery
MINDIST - elki.application.experiments.VisualizeGeodesicDistances.Mode: Mindist
minDistDeg(double, double, double, double, double, double) - Method in class elki.math.geodesy.AbstractEarthModel
minDistDeg(double, double, double, double, double, double) - Method in interface elki.math.geodesy.EarthModel: Compute a lower bound for the geodetic distance point to rectangle.
minDistLevel(DBID, int) - Method in class elki.outlier.distance.HilOut.HilbertFeatures: minDist function calculate the minimal Distance from Vector p to the border of the corresponding r-region at the given level
minDistObject(SpatialComparable, NumberVector) - Method in class elki.distance.subspace.SubspaceEuclideanDistance
minDistObject(SpatialComparable, NumberVector) - Method in class elki.distance.subspace.SubspaceLPNormDistance
minDistObject(SpatialComparable, NumberVector) - Method in class elki.distance.subspace.SubspaceManhattanDistance
minDistObject(SpatialComparable, NumberVector) - Method in class elki.distance.subspace.SubspaceMaximumDistance
minDistP - Variable in class elki.index.vafile.PartialVAFile.PartialVACandidate: (Current) minimum distance of this candidate.
minDistRad(double, double, double, double, double, double) - Method in class elki.math.geodesy.AbstractEarthModel
minDistRad(double, double, double, double, double, double) - Method in interface elki.math.geodesy.EarthModel: Compute a lower bound for the geodetic distance point to rectangle.
minDot(SpatialComparable, SpatialComparable) - Static method in class elki.data.VectorUtil: Compute the minimum angle between two rectangles, assuming unit length vectors
mindx - Variable in class elki.math.geometry.XYCurve: Drawing bounds for x
mindy - Variable in class elki.math.geometry.XYCurve: Drawing bounds for y
minHeap - Variable in class elki.clustering.kmeans.KMeansMinusMinus.Instance: Heap of the noise candidates.
MiniGUI - Class in elki.gui.minigui: Minimal GUI built around a table-based parameter editor.
MiniGUI() - Constructor for class elki.gui.minigui.MiniGUI: Constructor.
MiniGUI.SettingsComboboxModel - Class in elki.gui.minigui: Class to interface between the saved settings list and a JComboBox.
minima - Variable in class elki.algorithm.statistics.HopkinsStatisticClusteringTendency: Stores the minimum in each dimension.
minima - Variable in class elki.algorithm.statistics.HopkinsStatisticClusteringTendency.Par: Stores the minimum in each dimension.
minima - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization: Stores the minimum in each dimension.
minima - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization.Par: Stores the minimum in each dimension.
minima - Variable in class elki.datasource.filter.transform.PerturbationFilter: Stores the minimum in each dimension.
minima - Variable in class elki.datasource.filter.transform.PerturbationFilter.Par: Stores the minimum in each dimension.
MINIMA_ID - Static variable in class elki.algorithm.statistics.HopkinsStatisticClusteringTendency.Par: Parameter for minimum.
MINIMA_ID - Static variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization.Par: Parameter for minimum.
MINIMA_ID - Static variable in class elki.datasource.filter.transform.PerturbationFilter.Par: Parameter for minimum.
MinimalisticMemoryKDTree<O extends NumberVector> - Class in elki.index.tree.spatial.kd: Simple implementation of a static in-memory K-D-tree.
MinimalisticMemoryKDTree(Relation<O>, int) - Constructor for class elki.index.tree.spatial.kd.MinimalisticMemoryKDTree: Constructor.
MinimalisticMemoryKDTree.CountSortAccesses - Class in elki.index.tree.spatial.kd: Class to count object accesses during construction.
MinimalisticMemoryKDTree.Factory<O extends NumberVector> - Class in elki.index.tree.spatial.kd: Factory class
MinimalisticMemoryKDTree.Factory.Par<O extends NumberVector> - Class in elki.index.tree.spatial.kd: Parameterization class.
MinimalisticMemoryKDTree.KDTreeKNNSearcher - Class in elki.index.tree.spatial.kd: kNN query for the k-d-tree.
MinimalisticMemoryKDTree.KDTreePrioritySearcher - Class in elki.index.tree.spatial.kd: Priority search for the k-d-tree.
MinimalisticMemoryKDTree.KDTreeRangeSearcher - Class in elki.index.tree.spatial.kd: Range query for the k-d-tree.
MinimalisticMemoryKDTree.PrioritySearchBranch - Class in elki.index.tree.spatial.kd: Search position for priority search.
MinimalMarkers - Class in elki.visualization.style.marker: Simple marker library that just draws colored rectangles at the given coordinates.
MinimalMarkers(StyleLibrary) - Constructor for class elki.visualization.style.marker.MinimalMarkers: Constructor
MiniMax<O> - Class in elki.clustering.hierarchical: Minimax Linkage clustering.
MiniMax(Distance<? super O>) - Constructor for class elki.clustering.hierarchical.MiniMax: Constructor.
MiniMax.Instance - Class in elki.clustering.hierarchical: Main worker instance of MiniMax.
MiniMaxAnderberg<O> - Class in elki.clustering.hierarchical: This is a modification of the classic MiniMax algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
MiniMaxAnderberg(Distance<? super O>) - Constructor for class elki.clustering.hierarchical.MiniMaxAnderberg: Constructor.
MiniMaxAnderberg.Instance - Class in elki.clustering.hierarchical: Main worker instance of MiniMax.
MiniMaxNNChain<O> - Class in elki.clustering.hierarchical: MiniMax hierarchical clustering using the NNchain algorithm.
MiniMaxNNChain(Distance<? super O>) - Constructor for class elki.clustering.hierarchical.MiniMaxNNChain: Constructor.
MiniMaxNNChain.Instance - Class in elki.clustering.hierarchical: Main worker instance of MiniMaxNNChain.
MINIMUM - elki.clustering.correlation.cash.ParameterizationFunction.ExtremumType: Minimum.
MINIMUM_SUM - elki.clustering.hierarchical.HACAM.Variant: Minimum sum variant
MINIMUM_SUM_INCREASE - elki.clustering.hierarchical.HACAM.Variant: Minimum sum increase variant
MinimumDistance - Class in elki.distance.minkowski: Minimum distance for NumberVectors.
MinimumDistance() - Constructor for class elki.distance.minkowski.MinimumDistance: Deprecated.
Use static instance!
MinimumDistance.Par - Class in elki.distance.minkowski: Parameterization class.
MinimumEnlargementInsert<N extends AbstractMTreeNode<?,N,E>,E extends MTreeEntry> - Class in elki.index.tree.metrical.mtreevariants.strategies.insert: Minimum enlargement insert - default insertion strategy for the M-tree.
MinimumEnlargementInsert() - Constructor for class elki.index.tree.metrical.mtreevariants.strategies.insert.MinimumEnlargementInsert
MinimumVarianceLinkage - Class in elki.clustering.hierarchical.linkage: Minimum increase in variance (MIVAR) linkage.
MinimumVarianceLinkage() - Constructor for class elki.clustering.hierarchical.linkage.MinimumVarianceLinkage: Deprecated.
use the static instance MinimumVarianceLinkage.STATIC instead.
MinimumVarianceLinkage.Par - Class in elki.clustering.hierarchical.linkage: Class parameterizer.
minint - Variable in class elki.visualization.style.ClusterStylingPolicy: Intensity scaling
miniter - Variable in class elki.clustering.em.EM: Minimum number of iterations to do
miniter - Variable in class elki.clustering.em.EM.Par: Minimum number of iterations.
miniter - Variable in class elki.clustering.em.KDTreeEM: minimum amount of iterations
miniter - Variable in class elki.clustering.em.KDTreeEM.Par: Minimum number of iterations.
miniter - Variable in class elki.clustering.kmeans.FuzzyCMeans: Minimum number of iterations to do
miniter - Variable in class elki.clustering.kmeans.FuzzyCMeans.Par: Minimum number of iterations.
miniter - Variable in class elki.outlier.clustering.EMOutlier: Minimum number of iterations to do
miniter - Variable in class elki.outlier.clustering.EMOutlier.Par: Minimum number of iterations.
MINITER_ID - Static variable in class elki.clustering.em.EM.Par: Parameter to specify a minimum number of iterations.
MINITER_ID - Static variable in class elki.clustering.em.KDTreeEM.Par: Parameter to specify a minimum number of iterations
MINITER_ID - Static variable in class elki.clustering.kmeans.FuzzyCMeans.Par: Parameter to specify a minimum number of iterations
minlength - Variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm: Parameter for minimum and maximum length.
minlength - Variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm.Par: Parameter for minimum and maximum length.
MINLENGTH_ID - Static variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm.Par: Parameter to specify the minimum itemset length.
minmax - Variable in class elki.algorithm.statistics.AddSingleScale: Minimum and maximum to use.
minmax - Variable in class elki.algorithm.statistics.AddSingleScale.Par: Minimum and maximum to use.
minmax - Variable in class elki.parallel.processor.DoubleMinMaxProcessor.Instance: The central data store.
minmax - Variable in class elki.parallel.processor.DoubleMinMaxProcessor: The central data store.
MINMAX - elki.datasource.filter.transform.PerturbationFilter.ScalingReference
MINMAX_ID - Static variable in class elki.algorithm.statistics.AddSingleScale.Par: Minimum and maximum values.
minmaxRange(int, Relation<? extends NumberVector>, DBIDArrayIter, int, int) - Static method in class elki.index.tree.spatial.kd.split.SplitStrategy.Util: Find the minimum and maximum in each dimension of a range of values.
minmaxX - Variable in class elki.math.geometry.GrahamScanConvexHull2D: Min/Max in X
minmaxY - Variable in class elki.math.geometry.GrahamScanConvexHull2D: Min/Max in Y
minmeasure - Variable in class elki.itemsetmining.associationrules.AssociationRuleGeneration: Parameter for minimum interestingness measure.
minmeasure - Variable in class elki.itemsetmining.associationrules.AssociationRuleGeneration.Par: Parameter for minimum interestingness measure.
MINMEASURE_ID - Static variable in class elki.itemsetmining.associationrules.AssociationRuleGeneration.Par: Parameter to specify the minimum threshold for the interestingness measure.
minNMI() - Method in class elki.evaluation.clustering.Entropy: Get the min-normalized mutual information.
minpts - Variable in class elki.clustering.correlation.COPAC.Settings: MinPts parameter.
minpts - Variable in class elki.clustering.correlation.ERiC.Settings: Minimum neighborhood size (density).
minpts - Variable in class elki.clustering.correlation.FourC.Settings: MinPts / mu parameter.
minpts - Variable in class elki.clustering.dbscan.DBSCAN: Holds the minimum cluster size.
minpts - Variable in class elki.clustering.dbscan.DBSCAN.Par: Holds the minimum cluster size.
minpts - Variable in class elki.clustering.dbscan.GriDBSCAN.Instance: Holds the minimum cluster size.
minpts - Variable in class elki.clustering.dbscan.GriDBSCAN: Holds the minimum cluster size.
minpts - Variable in class elki.clustering.dbscan.predicates.MinPtsCorePredicate.Instance: The minpts parameter.
minpts - Variable in class elki.clustering.dbscan.predicates.MinPtsCorePredicate: The minpts parameter.
minpts - Variable in class elki.clustering.dbscan.predicates.MinPtsCorePredicate.Par: Minpts value
minpts - Variable in class elki.clustering.optics.AbstractOPTICS: The density threshold, in number of points.
minpts - Variable in class elki.clustering.optics.DeLiClu: Density threshold in number of objects.
minpts - Variable in class elki.clustering.optics.DeLiClu.Par: Minimum number of points.
minpts - Variable in class elki.clustering.SNNClustering: Minimum number of clusters for connectedness.
minpts - Variable in class elki.clustering.subspace.DiSH: OPTICS minPts parameter.
minpts - Variable in class elki.clustering.subspace.DiSH.Par: Threshold for minimum number of points in the neighborhood.
minpts - Variable in class elki.clustering.subspace.PreDeCon.Settings: DBSCAN Minpts parameter, aka "mu".
minpts - Variable in class elki.clustering.subspace.SUBCLU: Minimum number of points.
minpts - Variable in class elki.clustering.subspace.SUBCLU.Par: Minimum number of points.
minpts - Variable in class elki.outlier.OPTICSOF: Parameter to specify the threshold MinPts.
minpts - Variable in class elki.outlier.OPTICSOF.Par: Parameter to specify the threshold MinPts.
minPts - Variable in class elki.clustering.correlation.cash.CASHIntervalSplit: Minimum points.
minPts - Variable in class elki.clustering.correlation.CASH: Threshold for minimum number of points in a cluster
minPts - Variable in class elki.clustering.correlation.CASH.Par: Threshold for minimum number of points in a cluster
minPts - Variable in class elki.clustering.hierarchical.AbstractHDBSCAN: MinPts parameter.
minPts - Variable in class elki.clustering.optics.FastOPTICS: MinPts parameter.
minPts - Variable in class elki.clustering.uncertain.FDBSCAN.Par: MinPts of DBSCAN.
MINPTS_ID - Static variable in class elki.clustering.correlation.CASH.Par: Parameter to specify the threshold for minimum number of points in a cluster, must be an integer greater than 0.
MINPTS_ID - Static variable in class elki.clustering.dbscan.DBSCAN.Par: Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.
MINPTS_ID - Static variable in class elki.clustering.optics.DeLiClu.Par: Parameter to specify the threshold for minimum number of points within a cluster, must be an integer greater than 0.
MINPTS_ID - Static variable in class elki.clustering.subspace.DiSH.Par: Positive threshold for minimum numbers of points in the epsilon-neighborhood of a points.
MINPTS_ID - Static variable in class elki.clustering.subspace.SUBCLU.Par: Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0.
MinPtsCorePredicate - Class in elki.clustering.dbscan.predicates: The DBSCAN default core point predicate -- having at least MinPtsCorePredicate.minpts neighbors.
MinPtsCorePredicate(int) - Constructor for class elki.clustering.dbscan.predicates.MinPtsCorePredicate: Default constructor.
MinPtsCorePredicate.Instance - Class in elki.clustering.dbscan.predicates: Instance for a particular data set.
MinPtsCorePredicate.Par - Class in elki.clustering.dbscan.predicates: Parameterization class
minQuant - Variable in class elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier: Minimum and maximum number of samples.
minQuant - Variable in class elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier.Par: Minimum and maximum number of samples.
minr - Variable in class elki.utilities.datastructures.KuhnMunkres: Position of uncovered minimum row
minRegLevel(int, int) - Method in class elki.outlier.distance.HilOut.HilbertFeatures: minReg function calculate the minimal r-region level containing two points
minsigma - Variable in class elki.timeseries.SigniTrendChangeDetection: Minimum sigma to report.
minsigma - Variable in class elki.timeseries.SigniTrendChangeDetection.Par: Minimum sigma to report.
MINSIGMA_ID - Static variable in class elki.timeseries.SigniTrendChangeDetection.Par: Sigma reporting threshold.
minsize - Variable in class elki.clustering.correlation.LMCLUS: Minimum cluster size
minsize - Variable in class elki.clustering.correlation.LMCLUS.Par: Minimum cluster size.
MINSIZE_ID - Static variable in class elki.clustering.correlation.LMCLUS.Par: Parameter for the minimum cluster size
minSorting - Variable in class elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split: The entries sorted according to their min values of their MBRs.
minSplit - Variable in class elki.outlier.density.HySortOD.TreeStrategy: Minimum number of rows to allow sub-mapping.
minSplitSize - Variable in class elki.index.preprocessed.fastoptics.RandomProjectedNeighborsAndDensities: minimum size for which a point set is further partitioned (roughly corresponds to minPts in OPTICS)
minsupp - Variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm: Minimum support.
minsupp - Variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm.Par: Parameter for minimum support.
MINSUPP_ID - Static variable in class elki.itemsetmining.AbstractFrequentItemsetAlgorithm.Par: Parameter to specify the minimum support, in absolute or relative terms.
minus(double[][], double[][]) - Static method in class elki.math.linearalgebra.VMath: Component-wise matrix subtraction m3 = m1 - m2.
minus(double[], double) - Static method in class elki.math.linearalgebra.VMath: Subtract component-wise v1 - s1.
minus(double[], double[]) - Static method in class elki.math.linearalgebra.VMath: Computes component-wise v1 - v2.
minusEquals(double[][], double[][]) - Static method in class elki.math.linearalgebra.VMath: Component-wise matrix subtraction: m1 = m1 - m2, overwriting the existing matrix m1.
minusEquals(double[], double) - Static method in class elki.math.linearalgebra.VMath: Subtract component-wise in-place v1 = v1 - s1, overwriting the vector v1.
minusEquals(double[], double[]) - Static method in class elki.math.linearalgebra.VMath: Computes component-wise v1 = v1 - v2, overwriting the vector v1.
minusEquals(double[], NumberVector) - Static method in class elki.clustering.kmeans.AbstractKMeans: Similar to VMath.minusEquals, but accepts a number vector.
MinusLogGammaScaling - Class in elki.utilities.scaling.outlier: Scaling that can map arbitrary values to a probability in the range of [0:1], by assuming a Gamma distribution on the data and evaluating the Gamma CDF.
MinusLogGammaScaling() - Constructor for class elki.utilities.scaling.outlier.MinusLogGammaScaling: Constructor.
MinusLogGammaScaling.Par - Class in elki.utilities.scaling.outlier: Parameterization class.
MinusLogScaling - Class in elki.utilities.scaling: Scaling function to invert values by computing -1 * Math.log(x)
MinusLogScaling() - Constructor for class elki.utilities.scaling.MinusLogScaling
MinusLogStandardDeviationScaling - Class in elki.utilities.scaling.outlier: Scaling that can map arbitrary values to a probability in the range of [0:1].
MinusLogStandardDeviationScaling(double, double) - Constructor for class elki.utilities.scaling.outlier.MinusLogStandardDeviationScaling: Constructor.
MinusLogStandardDeviationScaling.Par - Class in elki.utilities.scaling.outlier: Parameterization class.
minusTimes(double[][], double[][], double) - Static method in class elki.math.linearalgebra.VMath: Component-wise matrix operation: m3 = m1 - m2 * s2
minusTimes(double[], double[], double) - Static method in class elki.math.linearalgebra.VMath: Computes component-wise v1 - v2 * s2.
minusTimesEquals(double[][], double[][], double) - Static method in class elki.math.linearalgebra.VMath: Component-wise matrix operation: m1 = m1 - m2 * s2, overwriting the existing matrix m1.
minusTimesEquals(double[], double[], double) - Static method in class elki.math.linearalgebra.VMath: Computes component-wise v1 = v1 - v2 * s2, overwriting the vector v1.
minValues - Variable in class elki.math.spacefillingcurves.ZCurveTransformer: Minimum values in each dimension.
minViolating(int[], double) - Method in class elki.svm.solver.Solver
minvote - Variable in class elki.application.greedyensemble.GreedyEnsembleExperiment: Minimum votes.
minwindow - Variable in class elki.clustering.onedimensional.KNNKernelDensityMinimaClustering: Window width, for local minima criterions.
minwindow - Variable in class elki.clustering.onedimensional.KNNKernelDensityMinimaClustering.Par: Window width, for local minima criterions.
minx - Variable in class elki.math.geometry.XYCurve: Minimum and maximum for X axis
minx - Variable in class elki.math.geometry.XYPlot: Minimum and maximum for X axis
minx - Variable in class elki.visualization.projections.CanvasSize: Minimum X
miny - Variable in class elki.math.geometry.XYCurve: Minimum and maximum for Y axis
miny - Variable in class elki.math.geometry.XYPlot: Minimum and maximum for Y axis
miny - Variable in class elki.visualization.projections.CanvasSize: Minimum Y
mipmaps - Variable in class elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Settings: Number of additional mipmaps to generate.
mirkin() - Method in class elki.evaluation.clustering.PairCounting: Computes the Mirkin index, aka Equivalence Mismatch Distance.
MissingPrerequisitesException - Exception in elki.utilities.exceptions: Exception thrown when prerequisites are not satisfied.
MissingPrerequisitesException(String) - Constructor for exception elki.utilities.exceptions.MissingPrerequisitesException: Constructor.
MissingPrerequisitesException(String, Throwable) - Constructor for exception elki.utilities.exceptions.MissingPrerequisitesException: Constructor.
miter - Variable in class elki.clustering.kmedoids.CLARANS.Assignment: Medoid iterator
MIter - Interface in elki.utilities.datastructures.iterator: Modifiable iterator, that also supports removal.
mixHashCodes(int...) - Static method in class elki.utilities.Util: Mix multiple hashcodes into one.
mixHashCodes(int, int) - Static method in class elki.utilities.Util: Mix multiple hashcodes into one.
mixHashCodes(int, int, int) - Static method in class elki.utilities.Util: Mix multiple hashcodes into one.
mixMagic(int, int) - Static method in class elki.persistent.OnDiskArray: Mix two magic numbers into one, to obtain a combined magic.
MixtureModelOutlierScaling - Class in elki.utilities.scaling.outlier: Tries to fit a mixture model (exponential for inliers and gaussian for outliers) to the outlier score distribution.
MixtureModelOutlierScaling() - Constructor for class elki.utilities.scaling.outlier.MixtureModelOutlierScaling
mj - Variable in class elki.clustering.hierarchical.MedoidLinkage.Instance: Iterators into medoid array.
MKAPPA - Static variable in class elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance: Minus Kappa constant.
MkAppDirectoryEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: Represents an entry in a directory node of a MkApp-Tree.
MkAppDirectoryEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppDirectoryEntry: Empty constructor for serialization purposes.
MkAppDirectoryEntry(DBID, double, int, double, PolynomialApproximation) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppDirectoryEntry: Constructor.
MkAppEntry - Interface in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: Defines the requirements for an entry in an MkCop-Tree node.
MkAppLeafEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: Represents an entry in a leaf node of a MkApp-Tree.
MkAppLeafEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppLeafEntry: Empty constructor for serialization purposes.
MkAppLeafEntry(DBID, double, PolynomialApproximation) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppLeafEntry: Constructor.
MkAppTree<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: MkAppTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
MkAppTree(Relation<O>, PageFile<MkAppTreeNode<O>>, MkAppTreeSettings<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree: Constructor.
MkAppTreeFactory<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: Factory for a MkApp-Tree
MkAppTreeFactory(PageFileFactory<?>, MkAppTreeSettings<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeFactory: Constructor.
MkAppTreeIndex<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: MkAppTree used as database index.
MkAppTreeIndex(Relation<O>, PageFile<MkAppTreeNode<O>>, MkAppTreeSettings<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeIndex: Constructor.
MkAppTreeNode<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: Represents a node in an MkApp-Tree.
MkAppTreeNode() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeNode: Empty constructor for Externalizable interface.
MkAppTreeNode(int, boolean) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeNode: Creates a MkAppTreeNode object.
MkAppTreeSettings<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkapp: Settings class for the MkApp Tree.
MkAppTreeSettings() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeSettings
MkCoPDirectoryEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkcop: Represents an entry in a directory node of an MkCop-Tree.
MkCoPDirectoryEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPDirectoryEntry: Empty constructor for serialization purposes.
MkCoPDirectoryEntry(DBID, double, int, double, ApproximationLine) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPDirectoryEntry: Constructor.
MkCoPEntry - Interface in elki.index.tree.metrical.mtreevariants.mktrees.mkcop: Defines the requirements for an entry in an MkCop-Tree node.
MkCoPLeafEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkcop: Represents an entry in a leaf node of a MkCoP-Tree.
MkCoPLeafEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPLeafEntry: Empty constructor for serialization purposes.
MkCoPLeafEntry(DBID, double, ApproximationLine, ApproximationLine) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPLeafEntry: Constructor.
MkCoPTree<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkcop: MkCopTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
MkCoPTree(Relation<O>, PageFile<MkCoPTreeNode<O>>, MkTreeSettings<O, MkCoPTreeNode<O>, MkCoPEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree: Constructor.
MkCopTreeFactory<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkcop: Factory for a MkCoPTree-Tree
MkCopTreeFactory(PageFileFactory<?>, MkTreeSettings<O, MkCoPTreeNode<O>, MkCoPEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCopTreeFactory: Constructor.
MkCoPTreeIndex<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkcop: MkCoPTree used as database index.
MkCoPTreeIndex(Relation<O>, PageFile<MkCoPTreeNode<O>>, MkTreeSettings<O, MkCoPTreeNode<O>, MkCoPEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTreeIndex: Constructor.
MkCoPTreeNode<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkcop: Represents a node in an MkCop-Tree.
MkCoPTreeNode() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTreeNode: Empty constructor for Externalizable interface.
MkCoPTreeNode(int, boolean) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTreeNode: Creates a MkCoPTreeNode object.
MkMaxDirectoryEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkmax: Represents an entry in a directory node of an MkMaxTree.
MkMaxDirectoryEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxDirectoryEntry: Empty constructor for serialization purposes.
MkMaxDirectoryEntry(DBID, double, int, double, double) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxDirectoryEntry: Constructor.
MkMaxEntry - Interface in elki.index.tree.metrical.mtreevariants.mktrees.mkmax: Defines the requirements for an entry in an MkMaxTreeNode .
MkMaxLeafEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkmax: Represents an entry in a leaf node of an MkMaxTree.
MkMaxLeafEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxLeafEntry: Empty constructor for serialization purposes.
MkMaxLeafEntry(DBID, double, double) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxLeafEntry: Constructor.
MkMaxTree<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkmax: MkMaxTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k <= k_max.
MkMaxTree(Relation<O>, PageFile<MkMaxTreeNode<O>>, MkTreeSettings<O, MkMaxTreeNode<O>, MkMaxEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTree: Constructor.
MkMaxTreeFactory<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkmax: Factory for MkMaxTrees
MkMaxTreeFactory(PageFileFactory<?>, MkTreeSettings<O, MkMaxTreeNode<O>, MkMaxEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeFactory: Constructor.
MkMaxTreeIndex<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkmax: MkMax tree
MkMaxTreeIndex(Relation<O>, PageFile<MkMaxTreeNode<O>>, MkTreeSettings<O, MkMaxTreeNode<O>, MkMaxEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeIndex: Constructor.
MkMaxTreeNode<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mkmax: Represents a node in an MkMaxTree.
MkMaxTreeNode() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeNode: Empty constructor for Externalizable interface.
MkMaxTreeNode(int, boolean) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeNode: Creates a new MkMaxTreeNode object.
MkTabDirectoryEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mktab: Represents an entry in a directory node of a MkTab-Tree.
MkTabDirectoryEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabDirectoryEntry: Empty constructor for serialization purposes.
MkTabDirectoryEntry(DBID, double, int, double, double[]) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabDirectoryEntry: Constructor.
MkTabEntry - Interface in elki.index.tree.metrical.mtreevariants.mktrees.mktab: Defines the requirements for an entry in an MkCop-Tree node.
MkTabLeafEntry - Class in elki.index.tree.metrical.mtreevariants.mktrees.mktab: Represents an entry in a leaf node of a MkTab-Tree.
MkTabLeafEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabLeafEntry: Empty constructor for serialization purposes.
MkTabLeafEntry(DBID, double, double[]) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabLeafEntry: Constructor.
MkTabTree<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mktab: MkTabTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
MkTabTree(Relation<O>, PageFile<MkTabTreeNode<O>>, MkTreeSettings<O, MkTabTreeNode<O>, MkTabEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree: Constructor.
MkTabTreeFactory<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mktab: Factory for MkTabTrees
MkTabTreeFactory(PageFileFactory<?>, MkTreeSettings<O, MkTabTreeNode<O>, MkTabEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeFactory: Constructor.
MkTabTreeFactory.Par<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mktab: Parameterization class.
MkTabTreeIndex<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mktab: MkTabTree used as database index.
MkTabTreeIndex(Relation<O>, PageFile<MkTabTreeNode<O>>, MkTreeSettings<O, MkTabTreeNode<O>, MkTabEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeIndex: Constructor.
MkTabTreeNode<O> - Class in elki.index.tree.metrical.mtreevariants.mktrees.mktab: Represents a node in a MkMax-Tree.
MkTabTreeNode() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeNode: Empty constructor for Externalizable interface.
MkTabTreeNode(int, boolean) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeNode: Creates a MkTabTreeNode object.
MkTreeHeader - Class in elki.index.tree.metrical.mtreevariants.mktrees: Encapsulates the header information for subclasses of AbstractMkTreeUnified.
MkTreeHeader() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.MkTreeHeader: Empty constructor for serialization.
MkTreeHeader(int, int, int, int) - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.MkTreeHeader: Creates a nerw header with the specified parameters.
MkTreeRKNNQuery<O> - Class in elki.index.tree.metrical.mtreevariants.query: Instance of a rKNN query for a particular spatial index.
MkTreeRKNNQuery(AbstractMkTree<O, ?, ?, ?>, DistanceQuery<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.query.MkTreeRKNNQuery: Constructor.
MkTreeSettings<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry> - Class in elki.index.tree.metrical.mtreevariants.mktrees: Class with settings for MkTrees.
MkTreeSettings() - Constructor for class elki.index.tree.metrical.mtreevariants.mktrees.MkTreeSettings
MLBDistSplit<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>> - Class in elki.index.tree.metrical.mtreevariants.strategies.split: Encapsulates the required methods for a split of a node in an M-Tree.
MLBDistSplit(DistributionStrategy) - Constructor for class elki.index.tree.metrical.mtreevariants.strategies.split.MLBDistSplit: Constructor.
mlogmax - Variable in class elki.utilities.scaling.outlier.MinusLogGammaScaling: Minimum value (after log step, so maximum again)
mlogmax - Variable in class elki.utilities.scaling.outlier.OutlierMinusLogScaling: Maximum -log value seen, set by OutlierMinusLogScaling.prepare(elki.result.outlier.OutlierResult)
mmacc - Variable in class elki.evaluation.clustering.ClusterContingencyTable: Maximum Matching Accuracy
MMRadSplit<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>> - Class in elki.index.tree.metrical.mtreevariants.strategies.split: Encapsulates the required methods for a split of a node in an M-Tree.
MMRadSplit(DistributionStrategy) - Constructor for class elki.index.tree.metrical.mtreevariants.strategies.split.MMRadSplit: Constructor.
mod - Variable in class elki.datasource.filter.typeconversions.WeightedUncertainSplitFilter: Modulo value for splitting.
modCount - Variable in class elki.utilities.datastructures.heap.Heap: (Structural) modification counter.
mode - Variable in class elki.application.experiments.VisualizeGeodesicDistances: Visualization mode.
mode - Variable in class elki.application.experiments.VisualizeGeodesicDistances.Par: Visualization mode.
mode - Variable in class elki.clustering.onedimensional.KNNKernelDensityMinimaClustering: Estimation modes.
mode - Variable in class elki.clustering.onedimensional.KNNKernelDensityMinimaClustering.Par: Estimation modes.
mode - Variable in class elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform: Mode.
mode - Variable in class elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform.Par: Mode.
mode - Variable in class elki.gui.util.ParameterTable.FileNameEditor: File selector mode.
mode - Variable in class elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization: Visualization mode.
mode - Variable in class elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization.Par: Drawing mode.
Mode() - Constructor for enum elki.application.experiments.VisualizeGeodesicDistances.Mode
Mode() - Constructor for enum elki.clustering.onedimensional.KNNKernelDensityMinimaClustering.Mode
Mode() - Constructor for enum elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform.Mode
Mode() - Constructor for enum elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Mode
Mode() - Constructor for enum elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Mode
Mode() - Constructor for enum elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization.Mode
Mode() - Constructor for enum elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization.Mode
Mode() - Constructor for enum elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Mode
Mode() - Constructor for enum elki.visualization.visualizers.silhouette.SilhouettePlotSelectionToolVisualization.Mode
MODE_ID - Static variable in class elki.application.experiments.VisualizeGeodesicDistances.Par: Visualization mode.
MODE_ID - Static variable in class elki.clustering.onedimensional.KNNKernelDensityMinimaClustering.Par: KDE mode.
MODE_ID - Static variable in class elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform.Par: Mode control.
MODE_ID - Static variable in class elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization.Par: Mode for drawing: Voronoi, Delaunay, both.
model - Variable in class elki.application.experiments.VisualizeGeodesicDistances: Earth model.
model - Variable in class elki.application.experiments.VisualizeGeodesicDistances.Par: Earth model to use.
model - Variable in class elki.data.Cluster: Cluster model.
model - Variable in class elki.data.projection.LatLngToECEFProjection: Earth model to use.
model - Variable in class elki.data.projection.LngLatToECEFProjection: Earth model to use
model - Variable in class elki.datasource.filter.transform.LatLngToECEFFilter: Earth model to use.
model - Variable in class elki.datasource.filter.transform.LngLatToECEFFilter: Earth model to use.
model - Variable in class elki.distance.geo.DimensionSelectingLatLngDistance: Earth model used.
model - Variable in class elki.distance.geo.DimensionSelectingLatLngDistance.Par: Earth model used.
model - Variable in class elki.distance.geo.LatLngDistance: Earth model to use.
model - Variable in class elki.distance.geo.LatLngDistance.Par: Earth model used.
model - Variable in class elki.distance.geo.LngLatDistance: Earth model to use.
model - Variable in class elki.distance.geo.LngLatDistance.Par: Earth model used.
model - Variable in class elki.gui.util.ParameterTable.ClassListEditor: Tree model
model - Variable in class elki.gui.util.TreePopup: Tree model.
model() - Method in interface elki.classification.Classifier: Produce a String representation of the classification model.
model() - Method in class elki.classification.KNNClassifier
model() - Method in class elki.classification.PriorProbabilityClassifier
Model - Class in elki.svm.model
Model - Interface in elki.data.model: Base interface for Model classes.
Model() - Constructor for class elki.svm.model.Model
MODEL_ID - Static variable in class elki.clustering.em.EM.Par: Parameter to specify the EM cluster models to use.
MODEL_ID - Static variable in interface elki.math.geodesy.EarthModel: Parameter to choose the earth model to use.
modelHeight - Variable in class elki.visualization.savedialog.SaveOptionsPanel
modelQual - Variable in class elki.visualization.savedialog.SaveOptionsPanel
models - Variable in class elki.clustering.em.KDTreeEM: Current clusters.
models - Variable in class elki.outlier.COP: Include models in output.
models - Variable in class elki.outlier.COP.Par: Include COP models
models - Variable in class elki.outlier.subspace.SOD: Report models.
models - Variable in class elki.outlier.subspace.SOD.Par: Track models.
MODELS_ID - Static variable in class elki.outlier.COP.Par: Include COP error vectors in output.
MODELS_ID - Static variable in class elki.outlier.subspace.SOD.Par: Parameter for keeping the models.
ModelUtil - Class in elki.data.model: Utility classes for dealing with cluster models.
ModelUtil() - Constructor for class elki.data.model.ModelUtil: Private constructor.
modelview - Variable in class elki.visualization.parallel3d.util.Simple1DOFCamera: GLU model view matrix
modelWidth - Variable in class elki.visualization.savedialog.SaveOptionsPanel
ModifiableDBIDs - Interface in elki.database.ids: Interface for a generic modifiable DBID collection.
ModifiableDoubleDBIDList - Interface in elki.database.ids: Modifiable API for Distance-DBID results
ModifiableHierarchy<O> - Interface in elki.utilities.datastructures.hierarchy: Modifiable Hierarchy.
ModifiableHyperBoundingBox - Class in elki.data: MBR class allowing modifications (as opposed to HyperBoundingBox).
ModifiableHyperBoundingBox() - Constructor for class elki.data.ModifiableHyperBoundingBox: Constructor.
ModifiableHyperBoundingBox(double[], double[]) - Constructor for class elki.data.ModifiableHyperBoundingBox: Creates a ModifiableHyperBoundingBox for the given hyper points.
ModifiableHyperBoundingBox(int, double, double) - Constructor for class elki.data.ModifiableHyperBoundingBox: Create a ModifiableHyperBoundingBox with given min and max.
ModifiableHyperBoundingBox(SpatialComparable) - Constructor for class elki.data.ModifiableHyperBoundingBox: Derive a bounding box from a spatial object.
ModifiableRelation<O> - Interface in elki.database.relation: Relations that allow modification.
modifyQP(double[], int, double, double) - Static method in class elki.math.linearalgebra.EigenvalueDecomposition
modifyQR(double[], int, boolean, double, double, double, double, double) - Static method in class elki.math.linearalgebra.EigenvalueDecomposition
MOMDistributionEstimator<D extends Distribution> - Interface in elki.math.statistics.distribution.estimator: Distribution estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.
momentumSwitch - Variable in class elki.projection.SNE: Iteration when to switch momentum.
momentumSwitch - Variable in class elki.projection.TSNE: Iteration when to switch momentum.
MOMEstimator - Class in elki.math.statistics.intrinsicdimensionality: Methods of moments estimator, using the first moment (i.e. average).
MOMEstimator() - Constructor for class elki.math.statistics.intrinsicdimensionality.MOMEstimator
MOMEstimator.Par - Class in elki.math.statistics.intrinsicdimensionality: Parameterization class.
momests - Variable in class elki.math.statistics.distribution.estimator.meta.BestFitEstimator: Mean and variance based estimators.
MONE - Static variable in class elki.svm.AbstractSingleSVM
mouseClicked(MouseEvent) - Method in class elki.gui.util.TreePopup.Handler
mouseClicked(MouseEvent) - Method in class elki.visualization.parallel3d.util.SimpleMenuOverlay
mouseDragged(MouseEvent) - Method in class elki.visualization.parallel3d.util.Arcball1DOFAdapter
mouseEntered(MouseEvent) - Method in class elki.gui.util.TreePopup.Handler
mouseEntered(MouseEvent) - Method in class elki.visualization.parallel3d.util.SimpleMenuOverlay
mouseExited(MouseEvent) - Method in class elki.gui.util.TreePopup.Handler
mouseExited(MouseEvent) - Method in class elki.visualization.parallel3d.util.SimpleMenuOverlay
mousePressed(MouseEvent) - Method in class elki.gui.util.TreePopup.Handler
mousePressed(MouseEvent) - Method in class elki.visualization.parallel3d.util.Arcball1DOFAdapter
mousePressed(MouseEvent) - Method in class elki.visualization.parallel3d.util.SimpleMenuOverlay
mouseReleased(MouseEvent) - Method in class elki.gui.util.TreePopup.Handler
mouseReleased(MouseEvent) - Method in class elki.visualization.parallel3d.util.SimpleMenuOverlay
mouseWheelMoved(MouseWheelEvent) - Method in class elki.visualization.parallel3d.util.Arcball1DOFAdapter
moveAxis(int, int) - Method in interface elki.visualization.projections.ProjectionParallel: shift a dimension to another position
moveAxis(int, int) - Method in class elki.visualization.projections.SimpleParallel
movedDistance(double[][], double[][], double[]) - Method in class elki.clustering.kmeans.AbstractKMeans.Instance: Maximum distance moved.
movedSimilarity(double[][], double[][], double[]) - Method in class elki.clustering.kmeans.spherical.SphericalKMeans.Instance: Similarity to previous locations.
MoveObjectsToolVisualization - Class in elki.visualization.visualizers.scatterplot.selection: Tool to move the currently selected objects.
MoveObjectsToolVisualization() - Constructor for class elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization: Constructor
MoveObjectsToolVisualization.Instance - Class in elki.visualization.visualizers.scatterplot.selection: Instance.
moveTo(double[]) - Method in class elki.visualization.svg.SVGPath: Move to the given coordinates.
moveTo(double, double) - Method in class elki.visualization.svg.SVGPath: Move to the given coordinates.
MRadSplit<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>> - Class in elki.index.tree.metrical.mtreevariants.strategies.split: Encapsulates the required methods for a split of a node in an M-Tree.
MRadSplit(DistributionStrategy) - Constructor for class elki.index.tree.metrical.mtreevariants.strategies.split.MRadSplit: Constructor.
msgformat - Variable in class elki.gui.util.LogPane: Formatter for regular messages (informational records)
msgformat - Variable in class elki.logging.CLISmartHandler: Formatter for regular messages (informational records)
msgStyle - Variable in class elki.gui.util.LogPane: Regular message style
MStepLevenbergMarquardt(double, double, long[], A, NumberArrayAdapter<?, A>) - Method in class elki.utilities.scaling.outlier.SigmoidOutlierScaling: M-Step using a modified Levenberg-Marquardt method.
MStepLevenbergMarquardt(double, double, ArrayDBIDs, long[], DoubleRelation) - Method in class elki.utilities.scaling.outlier.SigmoidOutlierScaling: M-Step using a modified Levenberg-Marquardt method.
mstPartition(double[][]) - Static method in class elki.index.tree.metrical.mtreevariants.strategies.split.MSTSplit: Partition the data using the minimum spanning tree.
MSTSplit<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>> - Class in elki.index.tree.metrical.mtreevariants.strategies.split: Splitting algorithm using the minimum spanning tree (MST), as proposed by the Slim-Tree variant.
MSTSplit() - Constructor for class elki.index.tree.metrical.mtreevariants.strategies.split.MSTSplit
mtag - Variable in class elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance: Element for the marker
mtag - Variable in class elki.visualization.visualizers.silhouette.SilhouettePlotSelectionToolVisualization.Instance: Element for the marker
mtag - Variable in class elki.visualization.visualizers.silhouette.SilhouettePlotSelectionVisualization.Instance: Element for the marker
MTree<O> - Class in elki.index.tree.metrical.mtreevariants.mtree: MTree is a metrical index structure based on the concepts of the M-Tree.
MTree(PageFile<MTreeNode<O>>, MTreeSettings<O, MTreeNode<O>, MTreeEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mtree.MTree: Constructor.
MTreeDirectoryEntry - Class in elki.index.tree.metrical.mtreevariants: Represents an entry in a directory node of an M-Tree.
MTreeDirectoryEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.MTreeDirectoryEntry: Empty constructor for serialization purposes.
MTreeDirectoryEntry(DBID, double, int, double) - Constructor for class elki.index.tree.metrical.mtreevariants.MTreeDirectoryEntry: Constructor.
MTreeEntry - Interface in elki.index.tree.metrical.mtreevariants: Defines the requirements for an entry in an M-Tree node.
MTreeFactory<O> - Class in elki.index.tree.metrical.mtreevariants.mtree: Factory for a M-Tree
MTreeFactory(PageFileFactory<?>, MTreeSettings<O, MTreeNode<O>, MTreeEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mtree.MTreeFactory: Constructor.
MTreeIndex<O> - Class in elki.index.tree.metrical.mtreevariants.mtree: Class for using an m-tree as database index.
MTreeIndex(Relation<O>, PageFile<MTreeNode<O>>, MTreeSettings<O, MTreeNode<O>, MTreeEntry>) - Constructor for class elki.index.tree.metrical.mtreevariants.mtree.MTreeIndex: Constructor.
MTreeInsert<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>> - Interface in elki.index.tree.metrical.mtreevariants.strategies.insert: Default insertion strategy for the M-tree.
MTreeKNNByDBID<O> - Class in elki.index.tree.metrical.mtreevariants.query: Instance of a KNN query for a particular spatial index.
MTreeKNNByDBID(AbstractMTree<O, ?, ?, ?>, DistanceQuery<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.query.MTreeKNNByDBID: Constructor.
MTreeKNNByObject<O> - Class in elki.index.tree.metrical.mtreevariants.query: Instance of a KNN query for a particular spatial index.
MTreeKNNByObject(AbstractMTree<O, ?, ?, ?>, DistanceQuery<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.query.MTreeKNNByObject: Constructor.
MTreeLeafEntry - Class in elki.index.tree.metrical.mtreevariants: Represents an entry in a leaf node of an M-Tree.
MTreeLeafEntry() - Constructor for class elki.index.tree.metrical.mtreevariants.MTreeLeafEntry: Empty constructor for serialization purposes.
MTreeLeafEntry(DBID, double) - Constructor for class elki.index.tree.metrical.mtreevariants.MTreeLeafEntry: Constructor.
MTreeNode<O> - Class in elki.index.tree.metrical.mtreevariants.mtree: Represents a node in an M-Tree.
MTreeNode() - Constructor for class elki.index.tree.metrical.mtreevariants.mtree.MTreeNode: Empty constructor for Externalizable interface.
MTreeNode(int, boolean) - Constructor for class elki.index.tree.metrical.mtreevariants.mtree.MTreeNode: Creates a new MTreeNode with the specified parameters.
MTreeRangeByDBID<O> - Class in elki.index.tree.metrical.mtreevariants.query: Instance of a range query for a particular spatial index.
MTreeRangeByDBID(AbstractMTree<O, ?, ?, ?>, DistanceQuery<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.query.MTreeRangeByDBID: Constructor.
MTreeRangeByObject<O> - Class in elki.index.tree.metrical.mtreevariants.query: Instance of a range query for a particular spatial index.
MTreeRangeByObject(AbstractMTree<O, ?, ?, ?>, DistanceQuery<O>) - Constructor for class elki.index.tree.metrical.mtreevariants.query.MTreeRangeByObject: Constructor.
MTreeSearchCandidate - Class in elki.index.tree.metrical.mtreevariants.query: Encapsulates the attributes for a object that can be stored in a heap.
MTreeSearchCandidate(double, int, DBID, double) - Constructor for class elki.index.tree.metrical.mtreevariants.query.MTreeSearchCandidate: Creates a new heap node with the specified parameters.
MTreeSettings<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry> - Class in elki.index.tree.metrical.mtreevariants: Class to store the MTree settings.
MTreeSettings() - Constructor for class elki.index.tree.metrical.mtreevariants.MTreeSettings
MTreeSplit<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>> - Interface in elki.index.tree.metrical.mtreevariants.strategies.split: Interface for M-tree splitting strategies.
mu - Variable in class elki.clustering.correlation.HiCO: Mu parameter.
mu - Variable in class elki.clustering.correlation.HiCO.Par: Mu parameter
mu - Variable in class elki.math.statistics.distribution.GeneralizedExtremeValueDistribution: Parameters (location, scale, shape)
mu - Variable in class elki.math.statistics.distribution.GeneralizedExtremeValueDistribution.Par: Parameters.
mu - Variable in class elki.math.statistics.distribution.GeneralizedParetoDistribution: Parameters (location, scale, shape)
mu - Variable in class elki.math.statistics.distribution.GeneralizedParetoDistribution.Par: Parameters.
mu - Variable in class elki.math.statistics.distribution.GumbelDistribution: Mode parameter mu.
mu - Variable in class elki.math.statistics.distribution.NormalDistribution.Par: Parameters.
mu - Variable in class elki.math.statistics.distribution.RayleighDistribution: Location parameter.
mu - Variable in class elki.utilities.scaling.outlier.MixtureModelOutlierScaling: Parameter mu of the gaussian distribution (outliers)
MU_ID - Static variable in class elki.clustering.correlation.HiCO.Par: Parameter to specify the smoothing factor, must be an integer greater than 0.
MU_ID - Static variable in class elki.clustering.subspace.DiSH.Par: Parameter that specifies the a minimum number of points as a smoothing factor to avoid the single-link-effect, must be an integer greater than 0.
MULT_MAX_ID - Static variable in class elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier.Par: Maximum quantity of generated samples.
MULT_MIN_ID - Static variable in class elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier.Par: Minimum quantity of generated samples.
MultiBorder - Class in elki.clustering.dbscan.util: Multiple border point assignment.
MultiBorder(Border, Border) - Constructor for class elki.clustering.dbscan.util.MultiBorder: Constructor.
multiclass_probability(int, double[][], double[]) - Static method in class elki.svm.model.ProbabilisticClassificationModel
MultidimensionalScalingMSTLayout3DPC - Class in elki.visualization.parallel3d.layout: Layout the axes by multi-dimensional scaling.
MultidimensionalScalingMSTLayout3DPC(Dependence) - Constructor for class elki.visualization.parallel3d.layout.MultidimensionalScalingMSTLayout3DPC: Constructor.
MultidimensionalScalingMSTLayout3DPC.Node - Class in elki.visualization.parallel3d.layout: Node class for this layout.
MultidimensionalScalingMSTLayout3DPC.Par - Class in elki.visualization.parallel3d.layout: Parameteriation class.
MultiLPNorm - Class in tutorial.distancefunction: Tutorial example Minowski-distance variation with different exponents for different dimensions for ELKI.
MultiLPNorm(double[]) - Constructor for class tutorial.distancefunction.MultiLPNorm: Constructor.
MultiLPNorm.Par - Class in tutorial.distancefunction: Parameterization class example
multiple - Variable in class elki.clustering.trivial.ByLabelClustering: Allow multiple cluster assignment.
multiple - Variable in class elki.clustering.trivial.ByLabelClustering.Par: Allow multiple cluster assignment.
MULTIPLE_ID - Static variable in class elki.clustering.trivial.ByLabelClustering.Par: Flag to indicate that multiple cluster assignment is possible.
multipleAssignment(Relation<?>) - Method in class elki.clustering.trivial.ByLabelClustering: Assigns the objects of the database to multiple clusters according to their labels.
multipleChangepointsWithConfidence(int, int) - Method in class elki.timeseries.OfflineChangePointDetectionAlgorithm.Instance: Performs multiple change point detection for a given time series.
MultipleFilesOutput - Class in elki.result.textwriter: Manage output to multiple files.
MultipleFilesOutput(Path) - Constructor for class elki.result.textwriter.MultipleFilesOutput: Constructor
MultipleFilesOutput(Path, boolean) - Constructor for class elki.result.textwriter.MultipleFilesOutput: Constructor
MultipleLinearRegression - Class in elki.math.statistics: Multiple linear regression attempts to model the relationship between two or more explanatory variables and a response variable by fitting a linear equation to observed data.
MultipleLinearRegression(double[], double[][]) - Constructor for class elki.math.statistics.MultipleLinearRegression: Constructor.
multipleNodeDeletion(double[][], ChengAndChurch.BiclusterCandidate) - Method in class elki.clustering.biclustering.ChengAndChurch: Algorithm 2 of Cheng and Church.
MultipleObjectsBundle - Class in elki.datasource.bundle: This class represents a set of "packaged" objects, which is a transfer container for objects, e.g., from parsers to a database.
MultipleObjectsBundle() - Constructor for class elki.datasource.bundle.MultipleObjectsBundle: Constructor.
MultipleObjectsBundleDatabaseConnection - Class in elki.datasource: Data source to feed a precomputed MultipleObjectsBundle into a database.
MultipleObjectsBundleDatabaseConnection(MultipleObjectsBundle) - Constructor for class elki.datasource.MultipleObjectsBundleDatabaseConnection: Constructor.
MultipleProjectionsLocalitySensitiveHashFunction - Class in elki.index.lsh.hashfunctions: LSH hash function for vector space data.
MultipleProjectionsLocalitySensitiveHashFunction(RandomProjectionFamily.Projection, double, Random) - Constructor for class elki.index.lsh.hashfunctions.MultipleProjectionsLocalitySensitiveHashFunction: Constructor.
MultiplicativeInverseScaling - Class in elki.utilities.scaling.outlier: Scaling function to invert values by computing 1/x, but in a variation that maps the values to the [0:1] interval and avoiding division by 0.
MultiplicativeInverseScaling() - Constructor for class elki.utilities.scaling.outlier.MultiplicativeInverseScaling: Constructor.
multiplicity - Variable in class elki.data.type.MultivariateSeriesTypeInformation: Number of variates per dimension.
multiplicity - Variable in class elki.datasource.filter.normalization.instancewise.InstanceMeanVarianceNormalization: Multiplicity of the vector.
multiplicity - Variable in class elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization: Multiplicity of the vector.
multiplier - Static variable in class elki.utilities.random.FastNonThreadsafeRandom
multiply(double[][], double[], double[]) - Method in class elki.datasource.filter.transform.FastMultidimensionalScalingTransform: Compute out = A * in, and return the (signed!)
MultiStepGUI - Class in elki.gui.multistep: Experimenter-style multi step GUI.
MultiStepGUI() - Constructor for class elki.gui.multistep.MultiStepGUI: Constructor
MULTIVARIATE_SERIES - Static variable in class elki.data.type.TypeUtil: Type request for multivariate time series.
MultivariateGaussianModel - Class in elki.clustering.em.models: Model for a single multivariate Gaussian cluster with arbitrary rotation.
MultivariateGaussianModel(double, double[]) - Constructor for class elki.clustering.em.models.MultivariateGaussianModel: Constructor.
MultivariateGaussianModel(double, double[], double[][]) - Constructor for class elki.clustering.em.models.MultivariateGaussianModel: Constructor.
MultivariateGaussianModelFactory - Class in elki.clustering.em.models: Factory for EM with multivariate Gaussian models (with covariance; also known as Gaussian Mixture Modeling, GMM).
MultivariateGaussianModelFactory(KMeansInitialization) - Constructor for class elki.clustering.em.models.MultivariateGaussianModelFactory: Constructor.
MultivariateSeriesTypeInformation<V extends FeatureVector<?>> - Class in elki.data.type: Type information for multi-variate time series.
MultivariateSeriesTypeInformation(FeatureVector.Factory<V, ?>, ByteBufferSerializer<? super V>, int, int, int) - Constructor for class elki.data.type.MultivariateSeriesTypeInformation: Constructor for an actual type.
MultivariateSeriesTypeInformation(Class<? super V>, int, int, int) - Constructor for class elki.data.type.MultivariateSeriesTypeInformation: Constructor for an actual type.
multivariateStandardization(double[]) - Method in class elki.datasource.filter.normalization.instancewise.InstanceMeanVarianceNormalization
MultivariateTimeSeriesFilter<V extends FeatureVector<?>> - Class in elki.datasource.filter.typeconversions: Class to "fold" a flat number vector into a multivariate time series.
MultivariateTimeSeriesFilter(int) - Constructor for class elki.datasource.filter.typeconversions.MultivariateTimeSeriesFilter: Constructor.
murmurMix32(int) - Static method in class elki.utilities.random.RandomFactory: MurmurHash3 mixing function.
murmurMix64(long) - Static method in class elki.utilities.random.RandomFactory: MurmurHash3 mixing function.
MutableProgress - Class in elki.logging.progress: Progress class with a moving target.
MutableProgress(String, int, Logging) - Constructor for class elki.logging.progress.MutableProgress: Constructor with logging.
mutation(ArrayList<AggarwalYuEvolutionary.Individuum>, double, double) - Method in class elki.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch: Apply the mutation algorithm.
mutualInformation - Variable in class elki.evaluation.clustering.Entropy: Mutual information (computed directly)
mutualInformation() - Method in class elki.evaluation.clustering.Entropy: Get the mutual information (not normalized, small values are good).
MutualInformationEquiwidthDependence - Class in elki.math.statistics.dependence: Mutual Information (MI) dependence measure by dividing each attribute into equal-width bins.
MutualInformationEquiwidthDependence() - Constructor for class elki.math.statistics.dependence.MutualInformationEquiwidthDependence: Constructor - use MutualInformationEquiwidthDependence.STATIC instance.
MutualInformationEquiwidthDependence.Par - Class in elki.math.statistics.dependence: Parameterization class.
mvCorDim - Variable in class elki.clustering.dbscan.predicates.FourCNeighborPredicate: Tool to help with parameterization.
mvpKNNSearch(KNNHeap, GNAT.Node, double) - Method in class elki.index.tree.metrical.vptree.GNAT.GNATKNNSearcher: Search the k nearest neighbors
mvpRangeSearch(ModifiableDoubleDBIDList, GNAT.Node, double) - Method in class elki.index.tree.metrical.vptree.GNAT.GNATRangeSearcher: Perform a range search on the MVP Tree
mvs - Variable in class elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization: Temporary storage used during initialization.
mvs - Variable in class elki.datasource.filter.transform.PerturbationFilter: Temporary storage used during initialization.
mvSize - Variable in class elki.clustering.dbscan.predicates.FourCNeighborPredicate: Tool to help with parameterization.
mvSize - Variable in class elki.clustering.dbscan.predicates.PreDeConNeighborPredicate: Tool to help with parameterization.
mvSize2 - Variable in class elki.clustering.dbscan.predicates.FourCNeighborPredicate: Tool to help with parameterization.
mvVar - Variable in class elki.clustering.dbscan.predicates.PreDeConNeighborPredicate: Tool to help with parameterization.
MWPRanking(int[]) - Constructor for class elki.math.statistics.dependence.mcde.MWPTest.MWPRanking: Constructor.
MWPTest - Class in elki.math.statistics.dependence.mcde: Implementation of Mann-Whitney U test returning the p-value (not the test statistic, thus MWP) for MCDEDependence.
MWPTest() - Constructor for class elki.math.statistics.dependence.mcde.MWPTest: Private Constructor - use MWPTest.STATIC
MWPTest.MWPRanking - Class in elki.math.statistics.dependence.mcde: Structure to hold values needed for computing MWP in MCDEDependene.
MWPTest.Par - Class in elki.math.statistics.dependence.mcde: Parameterizer, returning the static instance.

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