Uses of Class
elki.utilities.Priority

Packages that use Priority

Package	Description
elki.algorithm	Miscellaneous algorithms.
elki.classification	Classification algorithms.
elki.clustering	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.hierarchical.extraction	Extraction of partitional clusterings from hierarchical results.
elki.clustering.hierarchical.linkage	Linkages for hierarchical clustering.
elki.clustering.kmeans	K-means clustering and variations.
elki.clustering.kmeans.initialization	Initialization strategies for k-means.
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.subspace	Axis-parallel subspace clustering algorithms.
elki.clustering.trivial	Trivial clustering algorithms: all in one, no clusters, label clusterings.
elki.database.ids.integer	Integer-based DBID implementation -- do not use directly - always use DBIDUtil.
elki.database.query	Database queries - computing distances, neighbors, similarities - API and general documentation.
elki.datasource	Data normalization (and reconstitution) of data sets.
elki.datasource.filter.normalization.columnwise	Normalizations operating on columns / variates; where each column is treated independently.
elki.datasource.filter.transform	Data space transformations.
elki.distance	Distance functions for use within ELKI.
elki.distance.minkowski	Minkowski space Lp norms such as the popular Euclidean and Manhattan distances.
elki.distance.probabilistic	Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence, F-divergence, χ²-divergence, etc.
elki.index.tree.betula.distance	Distance functions for BETULA and BIRCH.
elki.index.tree.betula.features	Different variants of Betula and BIRCH cluster features.
elki.index.tree.metrical.covertree	Cover-tree variations.
elki.index.tree.metrical.mtreevariants.strategies.split	Splitting strategies of nodes in an M-tree (and variants).
elki.index.tree.spatial.kd	K-d-tree and variants.
elki.itemsetmining	Algorithms for frequent itemset mining such as APRIORI.
elki.math.statistics.dependence	Statistical measures of dependence, such as correlation.
elki.outlier.distance	Distance-based outlier detection algorithms, such as DBOutlier and kNN.
elki.outlier.lof	LOF family of outlier detection algorithms.
elki.outlier.trivial	Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
elki.projection	Data projections (see also preprocessing filters for basic projections).
elki.result	Result types, representation and handling.
elki.similarity.kernel	Kernel functions.
elki.timeseries	Algorithms for change point detection in time series.

Uses of Priority in elki.algorithm

Classes in elki.algorithm with annotations of type Priority

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	KNNJoin	Joins in a given spatial database to each object its k-nearest neighbors.

Uses of Priority in elki.classification

Classes in elki.classification with annotations of type Priority

Modifier and Type	Class	Description
class	KNNClassifier<O>	KNNClassifier classifies instances based on the class distribution among the k nearest neighbors in a database.

Uses of Priority in elki.clustering

Classes in elki.clustering with annotations of type Priority

Modifier and Type	Class	Description
class	BetulaLeafPreClustering	BETULA-based clustering algorithm that simply treats the leafs of the CFTree as clusters.

Uses of Priority in elki.clustering.dbscan

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

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	LSDBC<O extends NumberVector>	Locally Scaled Density Based Clustering.

Uses of Priority in elki.clustering.em

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

Modifier and Type	Class	Description
class	BetulaGMMWeighted	Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM), with optional MAP regularization.
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 Priority in elki.clustering.hierarchical

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

Modifier and Type	Class	Description
class	Anderberg<O>	This is a modification of the classic AGNES algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
class	MiniMaxAnderberg<O>	This is a modification of the classic MiniMax algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
class	SLINK<O>	Implementation of the efficient Single-Link Algorithm SLINK of R.

Uses of Priority in elki.clustering.hierarchical.extraction

Classes in elki.clustering.hierarchical.extraction with annotations of type Priority

Modifier and Type	Class	Description
class	ClustersWithNoiseExtraction	Extraction of a given number of clusters with a minimum size, and noise.
class	SimplifiedHierarchyExtraction	Extraction of simplified cluster hierarchies, as proposed in HDBSCAN.

Uses of Priority in elki.clustering.hierarchical.linkage

Classes in elki.clustering.hierarchical.linkage with annotations of type Priority

Modifier and Type	Class	Description
class	CompleteLinkage	Complete-linkage ("maximum linkage") clustering method.
class	FlexibleBetaLinkage	Flexible-beta linkage as proposed by Lance and Williams.
class	GroupAverageLinkage	Group-average linkage clustering method (UPGMA).
class	SingleLinkage	Single-linkage ("minimum") clustering method.
class	WardLinkage	Ward's method clustering method.
class	WeightedAverageLinkage	Weighted average linkage clustering method (WPGMA).

Uses of Priority in elki.clustering.kmeans

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

Modifier and Type	Class	Description
class	ExponionKMeans<V extends NumberVector>	Newlings's Exponion k-means algorithm, exploiting the triangle inequality.
class	ShallotKMeans<V extends NumberVector>	Borgelt's Shallot k-means algorithm, exploiting the triangle inequality.

Uses of Priority in elki.clustering.kmeans.initialization

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

Modifier and Type	Class	Description
class	RandomNormalGenerated	Initialize k-means by generating random vectors (normal distributed with \(N(\mu,\sigma)\) in each dimension).
class	RandomUniformGenerated	Initialize k-means by generating random vectors (uniform, within the value range of the data set).

Uses of Priority in elki.clustering.kmeans.spherical

Classes in elki.clustering.kmeans.spherical with annotations of type Priority

Modifier and Type	Class	Description
class	EuclideanSphericalElkanKMeans<V extends NumberVector>	Elkan's fast k-means by exploiting the triangle inequality in the corresponding Euclidean space.
class	EuclideanSphericalHamerlyKMeans<V extends NumberVector>	A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality in the corresponding Euclidean space.
class	EuclideanSphericalSimplifiedElkanKMeans<V extends NumberVector>	A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality in the corresponding Euclidean space.

Uses of Priority in elki.clustering.kmedoids

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

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	EagerPAM<O>	Variation of PAM that eagerly performs all swaps that yield an improvement during an iteration.
class	FastCLARANS<V>	A faster variation of CLARANS, that can explore O(k) as many swaps at a similar cost by considering all medoids for each candidate non-medoid.
class	FastPAM<O>	FastPAM: An improved version of PAM, that is usually O(k) times faster.
class	FastPAM1<O>	FastPAM1: A version of PAM that is O(k) times faster, i.e., now in O((n-k)²).
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.
class	SingleAssignmentKMedoids<O>	K-medoids clustering by using the initialization only, then assigning each object to the nearest neighbor.

Uses of Priority in elki.clustering.kmedoids.initialization

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

Modifier and Type	Class	Description
class	ParkJun<O>	Initialization method proposed by Park and Jun.

Uses of Priority in elki.clustering.optics

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

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 Priority in elki.clustering.silhouette

Classes in elki.clustering.silhouette with annotations of type Priority

Modifier and Type	Class	Description
class	FasterMSC<O>	Fast and Eager Medoid Silhouette Clustering.

Uses of Priority in elki.clustering.subspace

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

Modifier and Type	Class	Description
class	P3C	P3C: A Robust Projected Clustering Algorithm.

Uses of Priority in elki.clustering.trivial

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

Modifier and Type	Class	Description
class	ByLabelClustering	Pseudo clustering using labels.
class	ByLabelHierarchicalClustering	Pseudo clustering using labels.
class	ByLabelOrAllInOneClustering	Trivial class that will try to cluster by label, and fall back to an "all-in-one" clustering.
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 Priority in elki.database.ids.integer

Classes in elki.database.ids.integer with annotations of type Priority

Modifier and Type	Class	Description
class	TrivialDBIDFactory	Trivial DBID management, that never reuses IDs and just gives them out in sequence.

Uses of Priority in elki.database.query

Classes in elki.database.query with annotations of type Priority

Modifier and Type	Class	Description
class	DisableQueryOptimizer	Dummy implementation to disable automatic optimization.

Uses of Priority in elki.datasource

Classes in elki.datasource with annotations of type Priority

Modifier and Type	Class	Description
class	FileBasedDatabaseConnection	File based database connection based on the parser to be set.

Uses of Priority in elki.datasource.filter.normalization.columnwise

Classes in elki.datasource.filter.normalization.columnwise with annotations of type Priority

Modifier and Type	Class	Description
class	AttributeWiseMinMaxNormalization<V extends NumberVector>	Class to perform and undo a normalization on real vectors with respect to a given minimum and maximum in each dimension.
class	AttributeWiseVarianceNormalization<V extends NumberVector>	Class to perform and undo a normalization on real vectors with respect to given mean and standard deviation in each dimension.

Uses of Priority in elki.datasource.filter.transform

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

Modifier and Type	Class	Description
class	FastMultidimensionalScalingTransform<I,O extends NumberVector>	Rescale the data set using multidimensional scaling, MDS.
class	GlobalPrincipalComponentAnalysisTransform<O extends NumberVector>	Apply Principal Component Analysis (PCA) to the data set.

Uses of Priority in elki.distance

Classes in elki.distance with annotations of type Priority

Modifier and Type	Class	Description
class	ArcCosineDistance	Arcus cosine distance function for feature vectors.
class	CanberraDistance	Canberra distance function, a variation of Manhattan distance.
class	ClarkDistance	Clark distance function for vector spaces.
class	CosineDistance	Cosine distance function for feature vectors.
class	RandomStableDistance	This is a dummy distance providing random values (obviously not metrical), useful mostly for unit tests and baseline evaluations: obviously this distance provides no benefit whatsoever.

Uses of Priority in elki.distance.minkowski

Classes in elki.distance.minkowski with annotations of type Priority

Modifier and Type	Class	Description
class	EuclideanDistance	Euclidean distance for NumberVectors.
class	LPNormDistance	Lp-Norm (Minkowski norms) are a family of distances for NumberVectors.

Uses of Priority in elki.distance.probabilistic

Classes in elki.distance.probabilistic with annotations of type Priority

Modifier and Type	Class	Description
class	ChiDistance	χ distance function, symmetric version.
class	ChiSquaredDistance	χ² distance function, symmetric version.

Uses of Priority in elki.index.tree.betula.distance

Classes in elki.index.tree.betula.distance with annotations of type Priority

Modifier and Type	Class	Description
class	BIRCHAverageInterclusterDistance	Average intercluster distance.
class	BIRCHAverageIntraclusterDistance	Average intracluster distance.
class	BIRCHRadiusDistance	Average Radius (R) criterion.
class	BIRCHVarianceIncreaseDistance	Variance increase distance.

Uses of Priority in elki.index.tree.betula.features

Classes in elki.index.tree.betula.features with annotations of type Priority

Modifier and Type	Class	Description
static class	BIRCHCF.Factory	Factory for making cluster features.

Uses of Priority in elki.index.tree.metrical.covertree

Classes in elki.index.tree.metrical.covertree with annotations of type Priority

Modifier and Type	Class	Description
class	CoverTree<O>	Cover tree data structure (in-memory).

Uses of Priority in elki.index.tree.metrical.mtreevariants.strategies.split

Classes in elki.index.tree.metrical.mtreevariants.strategies.split with annotations of type Priority

Modifier and Type	Class	Description
class	MLBDistSplit<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>>	Encapsulates the required methods for a split of a node in an M-Tree.
class	MSTSplit<E extends MTreeEntry,N extends AbstractMTreeNode<?,N,E>>	Splitting algorithm using the minimum spanning tree (MST), as proposed by the Slim-Tree variant.

Uses of Priority in elki.index.tree.spatial.kd

Classes in elki.index.tree.spatial.kd with annotations of type Priority

Modifier and Type	Class	Description
class	MinimalisticMemoryKDTree<O extends NumberVector>	Simple implementation of a static in-memory K-D-tree.
class	SmallMemoryKDTree<O extends NumberVector>	Simple implementation of a static in-memory K-D-tree.

Uses of Priority in elki.itemsetmining

Classes in elki.itemsetmining with annotations of type Priority

Modifier and Type	Class	Description
class	FPGrowth	FP-Growth is an algorithm for mining the frequent itemsets by using a compressed representation of the database called FPGrowth.FPTree.

Uses of Priority in elki.math.statistics.dependence

Classes in elki.math.statistics.dependence with annotations of type Priority

Modifier and Type	Class	Description
class	DCor	Distance correlation.
class	HoughSpaceMeasure	HSM: Compute the "interestingness" of dimension connections using the Hough transformation.
class	PearsonCorrelationDependence	Pearson product-moment correlation coefficient.
class	SURFINGDependence	Compute the similarity of dimensions using the SURFING score.

Uses of Priority in elki.outlier.distance

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

Modifier and Type	Class	Description
class	KNNOutlier<O>	Outlier Detection based on the distance of an object to its k nearest neighbor.

Uses of Priority in elki.outlier.lof

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

Modifier and Type	Class	Description
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 Priority in elki.outlier.trivial

Classes in elki.outlier.trivial with annotations of type Priority

Modifier and Type	Class	Description
class	ByLabelOutlier	Trivial algorithm that marks outliers by their label.
class	TrivialAllOutlier	Trivial method that claims all objects to be outliers.
class	TrivialAverageCoordinateOutlier	Trivial method that takes the average of all dimensions (for one-dimensional data that is just the actual value!)
class	TrivialNoOutlier	Trivial method that claims to find no outliers.

Uses of Priority in elki.projection

Classes in elki.projection with annotations of type Priority

Modifier and Type	Class	Description
class	BarnesHutTSNE<O>	t-SNE using Barnes-Hut-Approximation.

Uses of Priority in elki.result

Classes in elki.result with annotations of type Priority

Modifier and Type	Class	Description
class	AutomaticVisualization	Handler to process and visualize a Result.
class	ResultWriter	Result handler that feeds the data into a TextWriter.

Uses of Priority in elki.similarity.kernel

Classes in elki.similarity.kernel with annotations of type Priority

Modifier and Type	Class	Description
class	LinearKernel	Linear Kernel function that computes a similarity between the two feature vectors x and y defined by \(x^T\cdot y\).
class	RadialBasisFunctionKernel	Gaussian radial basis function kernel (RBF Kernel).

Uses of Priority in elki.timeseries

Classes in elki.timeseries with annotations of type Priority

Modifier and Type	Class	Description
class	SigniTrendChangeDetection	Signi-Trend detection algorithm applies to a single time-series.