Uses of Class
elki.utilities.documentation.References

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.

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 Bezdek
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	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 for NumberVectors is a symmetric, smoothened version of the KullbackLeiblerDivergenceAsymmetricDistance.
class	JensenShannonDivergenceDistance	Jensen-Shannon Divergence for NumberVectors is a symmetric, smoothened version of the KullbackLeiblerDivergenceAsymmetricDistance.

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 Distance
class	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 distributed int 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 distributed int 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.