Uses of Class
elki.utilities.documentation.References
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Packages that use References Package Description elki.algorithm Miscellaneous algorithms.elki.clustering.dbscan DBSCAN and its generalizations.elki.clustering.em Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling (GMM).elki.clustering.hierarchical Hierarchical agglomerative clustering (HAC).elki.clustering.hierarchical.birch BIRCH clustering.elki.clustering.hierarchical.extraction Extraction of partitional clusterings from hierarchical results.elki.clustering.hierarchical.linkage Linkages for hierarchical clustering.elki.clustering.kcenter K-center clustering.elki.clustering.kmeans K-means clustering and variations.elki.clustering.kmeans.initialization Initialization strategies for k-means.elki.clustering.kmeans.quality Quality measures for k-Means results.elki.clustering.kmeans.spherical Spherical k-means clustering and variations.elki.clustering.kmedoids K-medoids clustering (PAM).elki.clustering.kmedoids.initialization elki.clustering.optics OPTICS family of clustering algorithms.elki.clustering.silhouette Silhouette clustering algorithms.elki.clustering.svm elki.data.uncertain Uncertain data objects.elki.distance Distance functions for use within ELKI.elki.distance.probabilistic Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence, F-divergence, χ²-divergence, etc.elki.evaluation.clustering Evaluation of clustering results.elki.evaluation.scores Evaluation of rankings and scorings.elki.index.idistance iDistance is a distance based indexing technique, using a reference points embedding.elki.index.lsh.hashfamilies Hash function families for LSH.elki.index.tree.betula BETULA clustering by aggregating the data into cluster features.elki.index.tree.betula.distance Distance functions for BETULA and BIRCH.elki.itemsetmining.associationrules.interest Association rule interestingness measures.elki.math Mathematical operations and utilities used throughout the framework.elki.math.linearalgebra.pca Principal Component Analysis (PCA) and eigenvector processing.elki.math.statistics Statistical tests and methods.elki.math.statistics.dependence Statistical measures of dependence, such as correlation.elki.math.statistics.distribution Standard distributions, with random generation functionalities.elki.math.statistics.intrinsicdimensionality Methods for estimating the intrinsic dimensionality.elki.math.statistics.tests Statistical tests.elki.outlier.distance Distance-based outlier detection algorithms, such as DBOutlier and kNN.elki.timeseries Algorithms for change point detection in time series.elki.utilities.datastructures Basic memory structures such as heaps and object hierarchies.elki.utilities.random Random number generation.elki.utilities.scaling.outlier Scaling of outlier scores, that require a statistical analysis of the occurring values. -
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Uses of References in elki.algorithm
Classes in elki.algorithm with annotations of type References Modifier and Type Class Description class
KNNDistancesSampler<O>
Provides an order of the kNN-distances for all objects within the database. -
Uses of References in elki.clustering.dbscan
Classes in elki.clustering.dbscan with annotations of type References Modifier and Type Class Description class
DBSCAN<O>
Density-Based Clustering of Applications with Noise (DBSCAN), an algorithm to find density-connected sets in a database. -
Uses of References in elki.clustering.em
Classes in elki.clustering.em with annotations of type References Modifier and Type Class Description class
EM<O,M extends MeanModel>
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM), with optional MAP regularization. -
Uses of References in elki.clustering.hierarchical
Classes in elki.clustering.hierarchical with annotations of type References Modifier and Type Class Description class
AGNES<O>
Hierarchical Agglomerative Clustering (HAC) or Agglomerative Nesting (AGNES) is a classic hierarchical clustering algorithm.class
MedoidLinkage<O>
Medoid linkage uses the distance of medoids as criterion.class
MiniMax<O>
Minimax Linkage clustering.class
MiniMaxNNChain<O>
MiniMax hierarchical clustering using the NNchain algorithm.class
NNChain<O>
NNchain clustering algorithm. -
Uses of References in elki.clustering.hierarchical.birch
Classes in elki.clustering.hierarchical.birch with annotations of type References Modifier and Type Class Description class
BIRCHLeafClustering
BIRCH-based clustering algorithm that simply treats the leafs of the CFTree as clusters.class
BIRCHLloydKMeans
BIRCH-based clustering algorithm that simply treats the leafs of the CFTree as clusters.class
CFTree
Partial implementation of the CFTree as used by BIRCH. -
Uses of References in elki.clustering.hierarchical.extraction
Classes in elki.clustering.hierarchical.extraction with annotations of type References Modifier and Type Class Description class
HDBSCANHierarchyExtraction
Extraction of simplified cluster hierarchies, as proposed in HDBSCAN, and additionally also compute the GLOSH outlier scores. -
Uses of References in elki.clustering.hierarchical.linkage
Classes in elki.clustering.hierarchical.linkage with annotations of type References Modifier and Type Class Description class
CompleteLinkage
Complete-linkage ("maximum linkage") clustering method.class
MinimumVarianceLinkage
Minimum increase in variance (MIVAR) linkage.class
WardLinkage
Ward's method clustering method. -
Uses of References in elki.clustering.kcenter
Classes in elki.clustering.kcenter with annotations of type References Modifier and Type Class Description class
GreedyKCenter<O>
Greedy algorithm for k-center algorithm also known as Gonzalez clustering, or farthest-first traversal. -
Uses of References in elki.clustering.kmeans
Classes in elki.clustering.kmeans with annotations of type References Modifier and Type Class Description class
AnnulusKMeans<V extends NumberVector>
Annulus k-means algorithm.class
FuzzyCMeans<V extends NumberVector>
Fuzzy Clustering developed by Dunn and revisited by Bezdekclass
KDTreeFilteringKMeans<V extends NumberVector>
Filtering or "blacklisting" K-means with k-d-tree acceleration.class
KDTreePruningKMeans<V extends NumberVector>
Pruning K-means with k-d-tree acceleration.class
LloydKMeans<V extends NumberVector>
The standard k-means algorithm, using bulk iterations and commonly attributed to Lloyd and Forgy (independently). -
Uses of References in elki.clustering.kmeans.initialization
Classes in elki.clustering.kmeans.initialization with annotations of type References Modifier and Type Class Description class
Ostrovsky
Ostrovsky initial means, a variant of k-means++ that is expected to give slightly better results on average, but only works for k-means and not for, e.g., PAM (k-medoids).class
RandomlyChosen<O>
Initialize K-means by randomly choosing k existing elements as initial cluster centers. -
Uses of References in elki.clustering.kmeans.quality
Classes in elki.clustering.kmeans.quality with annotations of type References Modifier and Type Class Description class
AkaikeInformationCriterion
Akaike Information Criterion (AIC). -
Uses of References in elki.clustering.kmeans.spherical
Classes in elki.clustering.kmeans.spherical with annotations of type References Modifier and Type Class Description class
SphericalElkanKMeans<V extends NumberVector>
Elkan's fast k-means by exploiting the triangle inequality.class
SphericalHamerlyKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality.class
SphericalSimplifiedElkanKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality.class
SphericalSimplifiedHamerlyKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality. -
Uses of References in elki.clustering.kmedoids
Classes in elki.clustering.kmedoids with annotations of type References Modifier and Type Class Description class
AlternatingKMedoids<O>
A k-medoids clustering algorithm, implemented as EM-style batch algorithm; known in literature as the "alternate" method.class
CLARA<V>
Clustering Large Applications (CLARA) is a clustering method for large data sets based on PAM, partitioning around medoids (PAM
) based on sampling.class
EagerPAM<O>
Variation of PAM that eagerly performs all swaps that yield an improvement during an iteration.class
PAM<O>
The original Partitioning Around Medoids (PAM) algorithm or k-medoids clustering, as proposed by Kaufman and Rousseeuw; a largely equivalent method was also proposed by Whitaker in the operations research domain, and is well known by the name "fast interchange" there. -
Uses of References in elki.clustering.kmedoids.initialization
Classes in elki.clustering.kmedoids.initialization with annotations of type References Modifier and Type Class Description class
AlternateRefinement<O>
Meta-Initialization for k-medoids by performing one (or many) k-means-style iteration.class
BUILD<O>
PAM initialization for k-means (and of course, for PAM). -
Uses of References in elki.clustering.optics
Classes in elki.clustering.optics with annotations of type References Modifier and Type Class Description class
OPTICSXi
Extract clusters from OPTICS plots using the original ξ (Xi) extraction, which defines steep areas if the reachability drops below 1-ξ, respectively increases to 1+ξ, of the current value, then constructs valleys that begin with a steep down, and end with a matching steep up area. -
Uses of References in elki.clustering.silhouette
Classes in elki.clustering.silhouette with annotations of type References Modifier and Type Class Description class
PAMMEDSIL<O>
Clustering to optimize the Medoid Silhouette coefficient with a PAM-based swap heuristic.class
PAMSIL<O>
Clustering to optimize the Silhouette coefficient with a PAM-based swap heuristic. -
Uses of References in elki.clustering.svm
Classes in elki.clustering.svm with annotations of type References Modifier and Type Class Description class
SupportVectorClustering
Support Vector Clustering works on SVDD, which tries to find the smallest sphere enclosing all objects in kernel space. -
Uses of References in elki.data.uncertain
Classes in elki.data.uncertain with annotations of type References Modifier and Type Class Description class
UnweightedDiscreteUncertainObject
Unweighted implementation of discrete uncertain objects.class
WeightedDiscreteUncertainObject
Weighted version of discrete uncertain objects. -
Uses of References in elki.distance
Classes in elki.distance with annotations of type References Modifier and Type Class Description class
BrayCurtisDistance
Bray-Curtis distance function / Sørensen–Dice coefficient for continuous vector spaces (not only binary data). -
Uses of References in elki.distance.probabilistic
Classes in elki.distance.probabilistic with annotations of type References Modifier and Type Class Description class
ChiDistance
χ distance function, symmetric version.class
FisherRaoDistance
Fisher-Rao riemannian metric for (discrete) probability distributions.class
HellingerDistance
Hellinger metric / affinity / kernel, Bhattacharyya coefficient, fidelity similarity, Matusita distance, Hellinger-Kakutani metric on a probability distribution.class
JeffreyDivergenceDistance
Jeffrey Divergence forNumberVector
s is a symmetric, smoothened version of theKullbackLeiblerDivergenceAsymmetricDistance
.class
JensenShannonDivergenceDistance
Jensen-Shannon Divergence forNumberVector
s is a symmetric, smoothened version of theKullbackLeiblerDivergenceAsymmetricDistance
. -
Uses of References in elki.evaluation.clustering
Classes in elki.evaluation.clustering with annotations of type References Modifier and Type Class Description class
BCubed
BCubed measures for cluster evaluation.class
Entropy
Entropy based measures, implemented using natural logarithms.Methods in elki.evaluation.clustering with annotations of type References Modifier and Type Method Description double
Entropy. arithmeticNMI()
Get the arithmetic averaged normalized mutual information. -
Uses of References in elki.evaluation.scores
Classes in elki.evaluation.scores with annotations of type References Modifier and Type Class Description class
AUPRCEvaluation
Compute the area under the precision-recall curve (AUPRC). -
Uses of References in elki.index.idistance
Classes in elki.index.idistance with annotations of type References Modifier and Type Class Description class
InMemoryIDistanceIndex<O>
In-memory iDistance index, a metric indexing method using a reference point embedding. -
Uses of References in elki.index.lsh.hashfamilies
Classes in elki.index.lsh.hashfamilies with annotations of type References Modifier and Type Class Description class
CosineHashFunctionFamily
Hash function family to use with Cosine distance, using simplified hash functions where the projection is only drawn from +-1, instead of Gaussian distributions. -
Uses of References in elki.index.tree.betula
Classes in elki.index.tree.betula with annotations of type References Modifier and Type Class Description class
CFTree<L extends ClusterFeature>
Partial implementation of the CFTree as used by BIRCH and BETULA. -
Uses of References in elki.index.tree.betula.distance
Classes in elki.index.tree.betula.distance with annotations of type References Modifier and Type Class Description class
AverageInterclusterDistance
Average intercluster distance.class
AverageIntraclusterDistance
Average intracluster distance.class
CentroidEuclideanDistance
Centroid Euclidean distance.class
CentroidManhattanDistance
Centroid Manhattan Distanceclass
RadiusDistance
Average Radius (R) criterion.class
VarianceIncreaseDistance
Variance increase distance. -
Uses of References in elki.itemsetmining.associationrules.interest
Classes in elki.itemsetmining.associationrules.interest with annotations of type References Modifier and Type Class Description class
GiniIndex
Gini-index based interestingness measure, using the weighted squared conditional probabilities compared to the non-conditional priors.class
Jaccard
Jaccard interestingness measure:class
LaplaceCorrectedConfidence
Laplace Corrected Confidence interestingness measure.class
OddsRatio
Odds ratio interestingness measure.class
PhiCorrelationCoefficient
Phi Correlation Coefficient interestingness measure.class
YulesQ
Yule's Q interestingness measure.class
YulesY
Yule's Y interestingness measure. -
Uses of References in elki.math
Classes in elki.math with annotations of type References Modifier and Type Class Description class
MeanVariance
Do some simple statistics (mean, variance) using a numerically stable online algorithm.class
StatisticalMoments
Track various statistical moments, including mean, variance, skewness and kurtosis. -
Uses of References in elki.math.linearalgebra.pca
Classes in elki.math.linearalgebra.pca with annotations of type References Modifier and Type Class Description class
RANSACCovarianceMatrixBuilder
RANSAC based approach to a more robust covariance matrix computation. -
Uses of References in elki.math.statistics
Classes in elki.math.statistics with annotations of type References Modifier and Type Class Description class
ProbabilityWeightedMoments
Estimate the L-Moments of a sample. -
Uses of References in elki.math.statistics.dependence
Classes in elki.math.statistics.dependence with annotations of type References Modifier and Type Class Description class
HiCSDependence
Use the statistical tests as used by HiCS to measure dependence of variables.class
SURFINGDependence
Compute the similarity of dimensions using the SURFING score. -
Uses of References in elki.math.statistics.distribution
Methods in elki.math.statistics.distribution with annotations of type References Modifier and Type Method Description static double
GammaDistribution. nextRandom(double k, double theta, java.util.Random random)
Generate a random value with the generators parameters. -
Uses of References in elki.math.statistics.intrinsicdimensionality
Classes in elki.math.statistics.intrinsicdimensionality with annotations of type References Modifier and Type Class Description class
LMomentsEstimator
Probability weighted moments based estimator using L-Moments.class
PWM2Estimator
Probability weighted moments based estimator, using the second moment.class
PWMEstimator
Probability weighted moments based estimator.class
ZipfEstimator
Zipf estimator (qq-estimator) of the intrinsic dimensionality. -
Uses of References in elki.math.statistics.tests
Classes in elki.math.statistics.tests with annotations of type References Modifier and Type Class Description class
StandardizedTwoSampleAndersonDarlingTest
Perform a two-sample Anderson-Darling rank test, and standardize the statistic according to Scholz and Stephens. -
Uses of References in elki.outlier.distance
Classes in elki.outlier.distance with annotations of type References Modifier and Type Class Description class
KNNSOS<O>
kNN-based adaption of Stochastic Outlier Selection. -
Uses of References in elki.timeseries
Classes in elki.timeseries with annotations of type References Modifier and Type Class Description class
OfflineChangePointDetectionAlgorithm
Off-line change point detection algorithm detecting a change in mean, based on the cumulative sum (CUSUM), same-variance assumption, and using bootstrap sampling for significance estimation. -
Uses of References in elki.utilities.datastructures
Classes in elki.utilities.datastructures with annotations of type References Modifier and Type Class Description class
KuhnMunkres
Kuhn-Munkres optimal matching (aka the Hungarian algorithm). -
Uses of References in elki.utilities.random
Methods in elki.utilities.random with annotations of type References Modifier and Type Method Description int
FastNonThreadsafeRandom. nextInt(int n)
Returns a pseudorandom, uniformly distributedint
value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.int
FastNonThreadsafeRandom. nextIntRefined(int n)
Returns a pseudorandom, uniformly distributedint
value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence. -
Uses of References in elki.utilities.scaling.outlier
Classes in elki.utilities.scaling.outlier with annotations of type References Modifier and Type Class Description class
COPOutlierScaling
CDF based outlier score scaling.
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