Uses of Class
elki.utilities.documentation.Title

Packages that use Title

Package	Description
elki.algorithm	Miscellaneous algorithms.
elki.algorithm.statistics	Statistical analysis algorithms.
elki.classification	Classification algorithms.
elki.clustering	Clustering algorithms.
elki.clustering.affinitypropagation	Affinity Propagation (AP) clustering.
elki.clustering.correlation	Correlation clustering 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.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.kmedoids	K-medoids clustering (PAM).
elki.clustering.kmedoids.initialization
elki.clustering.optics	OPTICS family of clustering algorithms.
elki.clustering.subspace	Axis-parallel subspace clustering algorithms.
elki.clustering.trivial	Trivial clustering algorithms: all in one, no clusters, label clusterings.
elki.clustering.uncertain	Clustering algorithms for uncertain data.
elki.datasource	Data normalization (and reconstitution) of data sets.
elki.datasource.filter.transform	Data space transformations.
elki.datasource.parser	Parsers for different file formats and data types.
elki.distance.timeseries	Distance functions designed for time series.
elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
elki.index.preprocessed.snn	Indexes providing nearest neighbor sets.
elki.index.projected	Projected indexes for data.
elki.index.tree.metrical.mtreevariants.mtree	MTree.
elki.index.tree.spatial.rstarvariants.rstar	RStarTree.
elki.index.vafile	Vector Approximation File.
elki.itemsetmining	Algorithms for frequent itemset mining such as APRIORI.
elki.math.linearalgebra	The linear algebra package provides classes and computational methods for operations on matrices and vectors.
elki.math.linearalgebra.pca	Principal Component Analysis (PCA) and eigenvector processing.
elki.math.linearalgebra.pca.filter	Filter eigenvectors based on their eigenvalues.
elki.outlier	Outlier detection algorithms.
elki.outlier.anglebased	Angle-based outlier detection algorithms.
elki.outlier.clustering	Clustering based outlier detection.
elki.outlier.density	Density-based outlier detection algorithms.
elki.outlier.distance	Distance-based outlier detection algorithms, such as DBOutlier and kNN.
elki.outlier.intrinsic	Outlier detection algorithms based on intrinsic dimensionality.
elki.outlier.lof	LOF family of outlier detection algorithms.
elki.outlier.meta	Meta outlier detection algorithms: external scores, score rescaling.
elki.outlier.spatial	Spatial outlier detection algorithms.
elki.outlier.subspace	Subspace outlier detection methods.
elki.projection	Data projections (see also preprocessing filters for basic projections).
elki.timeseries	Algorithms for change point detection in time series.
elki.visualization.visualizers.scatterplot.outlier	Visualizers for outlier scores based on 2D projections.

Packages with annotations of type Title

Package	Description
elki.clustering.em	Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling (GMM).
elki.clustering.kmeans.initialization	Initialization strategies for k-means.
elki.clustering.kmeans	K-means clustering and variations.
elki.outlier.spatial.neighborhood	Spatial outlier neighborhood classes.
elki.clustering.dbscan.parallel	Parallel versions of Generalized DBSCAN.
elki.clustering.kmeans.parallel	Parallelized implementations of k-means.
elki.outlier.distance.parallel	Parallel implementations of distance-based outlier detectors.
elki.outlier.lof.parallel	Parallelized variants of LOF.
elki.clustering.kmeans.quality	Quality measures for k-Means results.
elki.clustering.kmeans.spherical	Spherical k-means clustering and variations.

Uses of Title in elki.algorithm

Classes in elki.algorithm with annotations of type Title

Modifier and Type	Class	Description
class	DependencyDerivator<V extends NumberVector>	Dependency derivator computes quantitatively linear dependencies among attributes of a given dataset based on a linear correlation PCA.
class	KNNDistancesSampler<O>	Provides an order of the kNN-distances for all objects within the database.
class	KNNJoin	Joins in a given spatial database to each object its k-nearest neighbors.
class	NullAlgorithm	Null algorithm, which does nothing.

Uses of Title in elki.algorithm.statistics

Classes in elki.algorithm.statistics with annotations of type Title

Modifier and Type	Class	Description
class	DistanceStatisticsWithClasses<O>	Algorithm to gather statistics over the distance distribution in the data set.
class	EvaluateRankingQuality<V extends NumberVector>	Evaluate a distance function with respect to kNN queries.
class	RankingQualityHistogram<O>	Evaluate a distance function with respect to kNN queries.

Uses of Title in elki.classification

Classes in elki.classification with annotations of type Title

Modifier and Type	Class	Description
class	KNNClassifier<O>	KNNClassifier classifies instances based on the class distribution among the k nearest neighbors in a database.
class	PriorProbabilityClassifier	Classifier to classify instances based on the prior probability of classes in the database, without using the actual data values.

Uses of Title in elki.clustering

Classes in elki.clustering with annotations of type Title

Modifier and Type	Class	Description
class	SNNClustering<O>	Shared nearest neighbor clustering.

Uses of Title in elki.clustering.affinitypropagation

Classes in elki.clustering.affinitypropagation with annotations of type Title

Modifier and Type	Class	Description
class	AffinityPropagation<O>	Cluster analysis by affinity propagation.

Uses of Title in elki.clustering.correlation

Classes in elki.clustering.correlation with annotations of type Title

Modifier and Type	Class	Description
class	CASH	The CASH algorithm is a subspace clustering algorithm based on the Hough transform.
class	COPAC	COPAC is an algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary clustering algorithm over the partitions.
class	ERiC	Performs correlation clustering on the data partitioned according to local correlation dimensionality and builds a hierarchy of correlation clusters that allows multiple inheritance from the clustering result.
class	FourC	4C identifies local subgroups of data objects sharing a uniform correlation.
class	HiCO	Implementation of the HiCO algorithm, an algorithm for detecting hierarchies of correlation clusters.
class	ORCLUS	ORCLUS: Arbitrarily ORiented projected CLUSter generation.

Uses of Title in elki.clustering.dbscan

Classes in elki.clustering.dbscan with annotations of type Title

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.
class	GriDBSCAN<V extends NumberVector>	Using Grid for Accelerating Density-Based Clustering.
class	LSDBC<O extends NumberVector>	Locally Scaled Density Based Clustering.

Uses of Title in elki.clustering.em

Classes in elki.clustering.em with annotations of type Title

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 Title in elki.clustering.hierarchical

Classes in elki.clustering.hierarchical with annotations of type Title

Modifier and Type	Class	Description
class	HDBSCANLinearMemory<O>	Linear memory implementation of HDBSCAN clustering.
class	SLINK<O>	Implementation of the efficient Single-Link Algorithm SLINK of R.

Uses of Title in elki.clustering.kcenter

Classes in elki.clustering.kcenter with annotations of type Title

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 Title in elki.clustering.kmeans

Classes in elki.clustering.kmeans with annotations of type Title

Modifier and Type	Class	Description
class	CompareMeans<V extends NumberVector>	Compare-Means: Accelerated k-means by exploiting the triangle inequality and pairwise distances of means to prune candidate means.
class	GMeans<V extends NumberVector,M extends MeanModel>	G-Means extends K-Means and estimates the number of centers with Anderson Darling Test. Implemented as specialization of XMeans.
class	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	KMeansMinusMinus<V extends NumberVector>	k-means--: A Unified Approach to Clustering and Outlier Detection.
class	LloydKMeans<V extends NumberVector>	The standard k-means algorithm, using bulk iterations and commonly attributed to Lloyd and Forgy (independently).
class	MacQueenKMeans<V extends NumberVector>	The original k-means algorithm, using MacQueen style incremental updates; making this effectively an "online" (streaming) algorithm.
class	SortMeans<V extends NumberVector>	Sort-Means: Accelerated k-means by exploiting the triangle inequality and pairwise distances of means to prune candidate means (with sorting).
class	XMeans<V extends NumberVector,M extends MeanModel>	X-means: Extending K-means with Efficient Estimation on the Number of Clusters.

Uses of Title in elki.clustering.kmeans.initialization

Classes in elki.clustering.kmeans.initialization with annotations of type Title

Modifier and Type	Class	Description
class	AFKMC2	AFK-MC² initialization
class	KMC2	K-MC² initialization
class	KMeansPlusPlus<O>	K-Means++ initialization for k-means.
class	SphericalAFKMC2	Spherical K-Means++ initialization with markov chains.
class	SphericalKMeansPlusPlus<O>	Spherical K-Means++ initialization for k-means.

Uses of Title in elki.clustering.kmeans.quality

Classes in elki.clustering.kmeans.quality with annotations of type Title

Modifier and Type	Class	Description
class	BayesianInformationCriterionXMeans	Bayesian Information Criterion (BIC), also known as Schwarz criterion (SBC, SBIC) for the use with evaluating k-means results.

Uses of Title in elki.clustering.kmedoids

Classes in elki.clustering.kmedoids with annotations of type Title

Modifier and Type	Class	Description
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 Title in elki.clustering.kmedoids.initialization

Classes in elki.clustering.kmedoids.initialization with annotations of type Title

Modifier and Type	Class	Description
class	KMedoidsKMedoidsInitialization<O>	Initialize k-medoids with k-medoids, for methods such as PAMSIL. This could also be used to initialize, e.g., PAM with CLARA.

Uses of Title in elki.clustering.optics

Classes in elki.clustering.optics with annotations of type Title

Modifier and Type	Class	Description
class	DeLiClu<V extends NumberVector>	DeliClu: Density-Based Hierarchical Clustering
class	OPTICSHeap<O>	The OPTICS algorithm for density-based hierarchical clustering.
class	OPTICSList<O>	The OPTICS algorithm for density-based hierarchical clustering.
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 Title in elki.clustering.subspace

Classes in elki.clustering.subspace with annotations of type Title

Modifier and Type	Class	Description
class	CLIQUE	Implementation of the CLIQUE algorithm, a grid-based algorithm to identify dense clusters in subspaces of maximum dimensionality.
class	DiSH	Algorithm for detecting subspace hierarchies.
class	DOC	DOC is a sampling based subspace clustering algorithm.
class	FastDOC	The heuristic variant of the DOC algorithm, FastDOC
class	HiSC	Implementation of the HiSC algorithm, an algorithm for detecting hierarchies of subspace clusters.
class	P3C	P3C: A Robust Projected Clustering Algorithm.
class	PreDeCon	PreDeCon computes clusters of subspace preference weighted connected points.
class	PROCLUS	The PROCLUS algorithm, an algorithm to find subspace clusters in high dimensional spaces.
class	SUBCLU<V extends NumberVector>	Implementation of the SUBCLU algorithm, an algorithm to detect arbitrarily shaped and positioned clusters in subspaces.

Uses of Title in elki.clustering.trivial

Classes in elki.clustering.trivial with annotations of type Title

Modifier and Type	Class	Description
class	ByLabelClustering	Pseudo clustering using labels.
class	ByLabelHierarchicalClustering	Pseudo clustering using labels.
class	ByModelClustering	Pseudo clustering using annotated models.
class	TrivialAllInOne	Trivial pseudo-clustering that just considers all points to be one big cluster.
class	TrivialAllNoise	Trivial pseudo-clustering that just considers all points to be noise.

Uses of Title in elki.clustering.uncertain

Classes in elki.clustering.uncertain with annotations of type Title

Modifier and Type	Class	Description
class	CKMeans	Run k-means on the centers of each uncertain object.
class	FDBSCAN	FDBSCAN is an adaption of DBSCAN for fuzzy (uncertain) objects.
class	UKMeans	Uncertain K-Means clustering, using the average deviation from the center.

Uses of Title in elki.datasource

Classes in elki.datasource with annotations of type Title

Modifier and Type	Class	Description
class	EmptyDatabaseConnection	Pseudo database that is empty.
class	InputStreamDatabaseConnection	Database connection expecting input from an input stream such as stdin.

Uses of Title in elki.datasource.filter.transform

Classes in elki.datasource.filter.transform with annotations of type Title

Modifier and Type	Class	Description
class	PerturbationFilter<V extends NumberVector>	A filter to perturb the values by adding micro-noise.

Uses of Title in elki.datasource.parser

Classes in elki.datasource.parser with annotations of type Title

Modifier and Type	Class	Description
class	ArffParser	Parser to load WEKA .arff files into ELKI.
class	BitVectorLabelParser	Parser for parsing one BitVector per line, bits separated by whitespace.
class	LibSVMFormatParser<V extends SparseNumberVector>	Parser to read libSVM format files.
class	SparseNumberVectorLabelParser<V extends SparseNumberVector>	Parser for parsing one point per line, attributes separated by whitespace.
class	StringParser	Parser that loads a text file for use with string similarity measures.

Uses of Title in elki.distance.timeseries

Classes in elki.distance.timeseries with annotations of type Title

Modifier and Type	Class	Description
class	DerivativeDTWDistance	Derivative Dynamic Time Warping distance for numerical vectors.
class	DTWDistance	Dynamic Time Warping distance (DTW) for numerical vectors.
class	EDRDistance	Edit Distance on Real Sequence distance for numerical vectors.
class	ERPDistance	Edit Distance With Real Penalty distance for numerical vectors.
class	LCSSDistance	Longest Common Subsequence distance for numerical vectors.

Uses of Title in elki.index.preprocessed.knn

Classes in elki.index.preprocessed.knn with annotations of type Title

Modifier and Type	Class	Description
class	MaterializeKNNAndRKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors and the reverse k nearest neighbors (and their distances) to each database object.
class	MaterializeKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
class	MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends Node<E>,E extends MTreeEntry>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
class	PartitionApproximationMaterializeKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
class	SpatialApproximationMaterializeKNNPreprocessor<O extends NumberVector>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.

Uses of Title in elki.index.preprocessed.snn

Classes in elki.index.preprocessed.snn with annotations of type Title

Modifier and Type	Class	Description
class	SharedNearestNeighborPreprocessor<O>	A preprocessor for annotation of the ids of nearest neighbors to each database object.

Uses of Title in elki.index.projected

Classes in elki.index.projected with annotations of type Title

Modifier and Type	Class	Description
class	PINN<O extends NumberVector>	Projection-Indexed nearest-neighbors (PINN) is an index to retrieve the nearest neighbors in high dimensional spaces by using a random projection based index.

Uses of Title in elki.index.tree.metrical.mtreevariants.mtree

Classes in elki.index.tree.metrical.mtreevariants.mtree with annotations of type Title

Modifier and Type	Class	Description
class	MTree<O>	MTree is a metrical index structure based on the concepts of the M-Tree.

Uses of Title in elki.index.tree.spatial.rstarvariants.rstar

Classes in elki.index.tree.spatial.rstarvariants.rstar with annotations of type Title

Modifier and Type	Class	Description
class	RStarTree	RStarTree is a spatial index structure based on the concepts of the R*-Tree.

Uses of Title in elki.index.vafile

Classes in elki.index.vafile with annotations of type Title

Modifier and Type	Class	Description
class	VAFile<V extends NumberVector>	Vector-approximation file (VAFile)

Uses of Title in elki.itemsetmining

Classes in elki.itemsetmining with annotations of type Title

Modifier and Type	Class	Description
class	APRIORI	The APRIORI algorithm for Mining Association Rules.

Uses of Title in elki.math.linearalgebra

Classes in elki.math.linearalgebra with annotations of type Title

Modifier and Type	Class	Description
class	VMath	Class providing basic vector mathematics, for low-level vectors stored as double[].

Uses of Title in elki.math.linearalgebra.pca

Classes in elki.math.linearalgebra.pca with annotations of type Title

Modifier and Type	Class	Description
class	WeightedCovarianceMatrixBuilder	CovarianceMatrixBuilder with weights.

Uses of Title in elki.math.linearalgebra.pca.filter

Classes in elki.math.linearalgebra.pca.filter with annotations of type Title

Modifier and Type	Class	Description
class	DropEigenPairFilter	The "drop" filter looks for the largest drop in normalized relative eigenvalues.
class	FirstNEigenPairFilter	The FirstNEigenPairFilter marks the n highest eigenpairs as strong eigenpairs, where n is a user specified number.
class	LimitEigenPairFilter	The LimitEigenPairFilter marks all eigenpairs having an (absolute) eigenvalue below the specified threshold (relative or absolute) as weak eigenpairs, the others are marked as strong eigenpairs.
class	PercentageEigenPairFilter	The PercentageEigenPairFilter sorts the eigenpairs in descending order of their eigenvalues and marks the first eigenpairs, whose sum of eigenvalues is higher than the given percentage of the sum of all eigenvalues as strong eigenpairs.
class	ProgressiveEigenPairFilter	The ProgressiveEigenPairFilter sorts the eigenpairs in descending order of their eigenvalues and marks the first eigenpairs, whose sum of eigenvalues is higher than the given percentage of the sum of all eigenvalues as strong eigenpairs.
class	RelativeEigenPairFilter	The RelativeEigenPairFilter sorts the eigenpairs in descending order of their eigenvalues and marks the first eigenpairs who are a certain factor above the average of the remaining eigenvalues.
class	SignificantEigenPairFilter	The SignificantEigenPairFilter sorts the eigenpairs in descending order of their eigenvalues and chooses the contrast of an Eigenvalue to the remaining Eigenvalues is maximal.
class	WeakEigenPairFilter	The WeakEigenPairFilter sorts the eigenpairs in descending order of their eigenvalues and returns the first eigenpairs who are above the average mark as "strong", the others as "weak".

Uses of Title in elki.outlier

Classes in elki.outlier with annotations of type Title

Modifier and Type	Class	Description
class	COP<V extends NumberVector>	Correlation outlier probability: Outlier Detection in Arbitrarily Oriented Subspaces
class	DWOF<O>	Algorithm to compute dynamic-window outlier factors in a database based on a specified parameter k, which specifies the number of the neighbors to be considered during the calculation of the DWOF score.
class	GaussianModel	Outlier detection based on the probability density of the single normal distribution.
class	GaussianUniformMixture	Outlier detection algorithm using a mixture model approach.
class	OPTICSOF<O>	OPTICS-OF outlier detection algorithm, an algorithm to find Local Outliers in a database based on ideas from OPTICSTypeAlgorithm clustering.
class	SimpleCOP<V extends NumberVector>	Algorithm to compute local correlation outlier probability.

Uses of Title in elki.outlier.anglebased

Classes in elki.outlier.anglebased with annotations of type Title

Modifier and Type	Class	Description
class	ABOD<V extends NumberVector>	Angle-Based Outlier Detection / Angle-Based Outlier Factor.
class	FastABOD<V extends NumberVector>	Fast-ABOD (approximateABOF) version of Angle-Based Outlier Detection / Angle-Based Outlier Factor.
class	LBABOD<V extends NumberVector>	LB-ABOD (lower-bound) version of Angle-Based Outlier Detection / Angle-Based Outlier Factor.

Uses of Title in elki.outlier.clustering

Classes in elki.outlier.clustering with annotations of type Title

Modifier and Type	Class	Description
class	CBLOF<O extends NumberVector>	Cluster-based local outlier factor (CBLOF).
class	DBSCANOutlierDetection	Outlier detection algorithm using DBSCAN Clustering.
class	EMOutlier<V extends NumberVector>	Outlier detection algorithm using EM Clustering.
class	GLOSH	Global-Local Outlier Scores from Hierarchies.
class	KMeansMinusMinusOutlierDetection	k-means--: A Unified Approach to Clustering and Outlier Detection.

Uses of Title in elki.outlier.density

Classes in elki.outlier.density with annotations of type Title

Modifier and Type	Class	Description
class	HySortOD	Hypercube-Based Outlier Detection.

Uses of Title in elki.outlier.distance

Classes in elki.outlier.distance with annotations of type Title

Modifier and Type	Class	Description
class	DBOutlierDetection<O>	Simple distanced based outlier detection algorithm.
class	DBOutlierScore<O>	Compute percentage of neighbors in the given neighborhood with size d.
class	HilOut<O extends NumberVector>	Fast Outlier Detection in High Dimensional Spaces
class	KNNDD<O>	Nearest Neighbor Data Description.
class	KNNOutlier<O>	Outlier Detection based on the distance of an object to its k nearest neighbor.
class	KNNSOS<O>	kNN-based adaption of Stochastic Outlier Selection.
class	KNNWeightOutlier<O>	Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.
class	ODIN<O>	Outlier detection based on the in-degree of the kNN graph.
class	ReferenceBasedOutlierDetection	Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.
class	SOS<O>	Stochastic Outlier Selection.

Uses of Title in elki.outlier.intrinsic

Classes in elki.outlier.intrinsic with annotations of type Title

Modifier and Type	Class	Description
class	IDOS<O>	Intrinsic Dimensional Outlier Detection in High-Dimensional Data.
class	ISOS<O>	Intrinsic Stochastic Outlier Selection.
class	LID<O>	Use intrinsic dimensionality for outlier detection.

Uses of Title in elki.outlier.lof

Classes in elki.outlier.lof with annotations of type Title

Modifier and Type	Class	Description
class	ALOCI<V extends NumberVector>	Fast Outlier Detection Using the "approximate Local Correlation Integral".
class	COF<O>	Connectivity-based Outlier Factor (COF).
class	FlexibleLOF<O>	Flexible variant of the "Local Outlier Factor" algorithm.
class	INFLO<O>	Influence Outliers using Symmetric Relationship (INFLO) using two-way search, is an outlier detection method based on LOF; but also using the reverse kNN.
class	KDEOS<O>	Generalized Outlier Detection with Flexible Kernel Density Estimates.
class	LDF<O extends NumberVector>	Outlier Detection with Kernel Density Functions.
class	LDOF<O>	Computes the LDOF (Local Distance-Based Outlier Factor) for all objects of a Database.
class	LOCI<O>	Fast Outlier Detection Using the "Local Correlation Integral".
class	LOF<O>	Algorithm to compute density-based local outlier factors in a database based on a specified parameter -lof.k.
class	LoOP<O>	LoOP: Local Outlier Probabilities

Uses of Title in elki.outlier.meta

Classes in elki.outlier.meta with annotations of type Title

Modifier and Type	Class	Description
class	FeatureBagging	A simple ensemble method called "Feature bagging" for outlier detection.
class	HiCS	Algorithm to compute High Contrast Subspaces for Density-Based Outlier Ranking.

Uses of Title in elki.outlier.spatial

Classes in elki.outlier.spatial with annotations of type Title

Modifier and Type	Class	Description
class	CTLuGLSBackwardSearchAlgorithm<V extends NumberVector>	GLS-Backward Search is a statistical approach to detecting spatial outliers.
class	CTLuMedianAlgorithm<N>	Median Algorithm of C.
class	CTLuMoranScatterplotOutlier<N>	Moran scatterplot outliers, based on the standardized deviation from the local and global means.
class	CTLuRandomWalkEC<O>	Spatial outlier detection based on random walks.
class	CTLuScatterplotOutlier<N>	Scatterplot-outlier is a spatial outlier detection method that performs a linear regression of object attributes and their neighbors average value.
class	CTLuZTestOutlier<N>	Detect outliers by comparing their attribute value to the mean and standard deviation of their neighborhood.
class	SLOM<N,O>	SLOM: a new measure for local spatial outliers
class	SOF<N,O>	The Spatial Outlier Factor (SOF) is a spatial LOF variation.
class	TrimmedMeanApproach<N>	A Trimmed Mean Approach to Finding Spatial Outliers.

Uses of Title in elki.outlier.subspace

Classes in elki.outlier.subspace with annotations of type Title

Modifier and Type	Class	Description
class	AggarwalYuEvolutionary	Evolutionary variant (EAFOD) of the high-dimensional outlier detection algorithm by Aggarwal and Yu.
class	AggarwalYuNaive	BruteForce variant of the high-dimensional outlier detection algorithm by Aggarwal and Yu.
class	OutRankS1	OutRank: ranking outliers in high dimensional data.
class	SOD<V extends NumberVector>	Subspace Outlier Degree: Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data.

Uses of Title in elki.projection

Classes in elki.projection with annotations of type Title

Modifier and Type	Class	Description
class	BarnesHutTSNE<O>	t-SNE using Barnes-Hut-Approximation.
class	IntrinsicNearestNeighborAffinityMatrixBuilder<O>	Build sparse affinity matrix using the nearest neighbors only, adjusting for intrinsic dimensionality.
class	TSNE<O>	t-Stochastic Neighbor Embedding is a projection technique designed for visualization that tries to preserve the nearest neighbor structure.

Uses of Title in elki.timeseries

Classes in elki.timeseries with annotations of type Title

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.
class	SigniTrendChangeDetection	Signi-Trend detection algorithm applies to a single time-series.

Uses of Title in elki.visualization.visualizers.scatterplot.outlier

Classes in elki.visualization.visualizers.scatterplot.outlier with annotations of type Title

Modifier and Type	Class	Description
class	COPVectorVisualization	Visualize error vectors as produced by COP.