Uses of Class
elki.utilities.documentation.Description

Packages that use Description

Package	Description
elki.algorithm	Miscellaneous algorithms.
elki.algorithm.statistics	Statistical analysis algorithms.
elki.classification	Classification algorithms.
elki.clustering	Clustering algorithms.
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.kmedoids.initialization
elki.clustering.meta	Meta clustering algorithms, that get their result from other clusterings or external sources.
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.database	ELKI database layer - loading, storing, indexing and accessing 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.strings	Distance functions for strings.
elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
elki.index.preprocessed.snn	Indexes providing nearest neighbor sets.
elki.index.tree.metrical.mtreevariants.mtree	MTree.
elki.index.tree.spatial.rstarvariants.rstar	RStarTree.
elki.itemsetmining	Algorithms for frequent itemset mining such as APRIORI.
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.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.result	Result types, representation and handling.
elki.timeseries	Algorithms for change point detection in time series.

Uses of Description in elki.algorithm

Classes in elki.algorithm with annotations of type Description

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 Description in elki.algorithm.statistics

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

Modifier and Type	Class	Description
class	AddSingleScale	Pseudo "algorithm" that computes the global min/max for a relation across all attributes.
class	AddUniformScale	Pseudo "algorithm" that computes the global min/max for a relation across all attributes.
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 Description in elki.classification

Classes in elki.classification with annotations of type Description

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 Description in elki.clustering

Classes in elki.clustering with annotations of type Description

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

Uses of Description in elki.clustering.correlation

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

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 Description in elki.clustering.dbscan

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

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 Description in elki.clustering.em

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

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.
class	KDTreeEM	Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM), calculated on a kd-tree.

Uses of Description in elki.clustering.hierarchical

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

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 Description in elki.clustering.kmedoids.initialization

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

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 Description in elki.clustering.meta

Classes in elki.clustering.meta with annotations of type Description

Modifier and Type	Class	Description
class	ExternalClustering	Read an external clustering result from a file, such as produced by ClusteringVectorDumper.

Uses of Description in elki.clustering.optics

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

Modifier and Type	Class	Description
class	DeLiClu<V extends NumberVector>	DeliClu: Density-Based Hierarchical Clustering

Uses of Description in elki.clustering.subspace

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

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	HiSC	Implementation of the HiSC algorithm, an algorithm for detecting hierarchies of subspace clusters.
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 Description in elki.clustering.trivial

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

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 Description in elki.clustering.uncertain

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

Modifier and Type	Class	Description
class	FDBSCAN	FDBSCAN is an adaption of DBSCAN for fuzzy (uncertain) objects.

Uses of Description in elki.database

Classes in elki.database with annotations of type Description

Modifier and Type	Class	Description
class	HashmapDatabase	Database storing data using hashtable storage, and thus allowing additional and removal of objects.
class	StaticArrayDatabase	This database class uses array-based storage and thus does not allow for dynamic insert, delete and update operations.

Uses of Description in elki.datasource

Classes in elki.datasource with annotations of type Description

Modifier and Type	Class	Description
class	DBIDRangeDatabaseConnection	This is a fake datasource that produces a static DBID range only.
class	EmptyDatabaseConnection	Pseudo database that is empty.
class	InputStreamDatabaseConnection	Database connection expecting input from an input stream such as stdin.
class	PresortedBlindJoinDatabaseConnection	Joins multiple data sources by their existing order.

Uses of Description in elki.datasource.filter.transform

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

Modifier and Type	Class	Description
class	HistogramJitterFilter<V extends NumberVector>	Add jitter, preserving the histogram properties (same sum, nonnegative).
class	PerturbationFilter<V extends NumberVector>	A filter to perturb the values by adding micro-noise.

Uses of Description in elki.datasource.parser

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

Modifier and Type	Class	Description
class	BitVectorLabelParser	Parser for parsing one BitVector per line, bits separated by whitespace.
class	CategorialDataAsNumberVectorParser<V extends NumberVector>	A very simple parser for categorial data, which will then be encoded as numbers.
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 Description in elki.distance.strings

Classes in elki.distance.strings with annotations of type Description

Modifier and Type	Class	Description
class	LevenshteinDistance	Classic Levenshtein distance on strings.
class	NormalizedLevenshteinDistance	Levenshtein distance on strings, normalized by string length.

Uses of Description in elki.index.preprocessed.knn

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

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 Description in elki.index.preprocessed.snn

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

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

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

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

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

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

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

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

Uses of Description in elki.itemsetmining

Classes in elki.itemsetmining with annotations of type Description

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

Uses of Description in elki.math.linearalgebra.pca

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

Modifier and Type	Class	Description
class	WeightedCovarianceMatrixBuilder	CovarianceMatrixBuilder with weights.

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

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

Modifier and Type	Class	Description
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 Description in elki.outlier

Classes in elki.outlier with annotations of type Description

Modifier and Type	Class	Description
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.

Uses of Description in elki.outlier.anglebased

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

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 Description in elki.outlier.clustering

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

Modifier and Type	Class	Description
class	EMOutlier<V extends NumberVector>	Outlier detection algorithm using EM Clustering.
class	GLOSH	Global-Local Outlier Scores from Hierarchies.

Uses of Description in elki.outlier.density

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

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

Uses of Description in elki.outlier.distance

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

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	KNNOutlier<O>	Outlier Detection based on the distance of an object to its k nearest neighbor.
class	KNNWeightOutlier<O>	Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.
class	ReferenceBasedOutlierDetection	Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.

Uses of Description in elki.outlier.lof

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

Modifier and Type	Class	Description
class	ALOCI<V extends NumberVector>	Fast Outlier Detection Using the "approximate Local Correlation Integral".
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	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 Description in elki.outlier.meta

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

Modifier and Type	Class	Description
class	HiCS	Algorithm to compute High Contrast Subspaces for Density-Based Outlier Ranking.

Uses of Description in elki.outlier.spatial

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

Modifier and Type	Class	Description
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	TrimmedMeanApproach<N>	A Trimmed Mean Approach to Finding Spatial Outliers.

Uses of Description in elki.outlier.subspace

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

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 Description in elki.result

Classes in elki.result with annotations of type Description

Modifier and Type	Class	Description
class	LogResultStructureResultHandler	A result handler to help with ELKI development that will just show the structure of the result object.

Uses of Description in elki.timeseries

Classes in elki.timeseries with annotations of type Description

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.