Uses of Class
de.lmu.ifi.dbs.elki.logging.AbstractLoggable

Packages that use AbstractLoggable

de.lmu.ifi.dbs.elki	The base-package of the ELKI framework.
de.lmu.ifi.dbs.elki.algorithm	Package to collect algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering	Package collects clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering	Package to collect biclustering algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Package to collect correlation clustering algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash	Helper classes for the CASH algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Package to collect algorithms for clustering in axis-parallel subspaces, suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.result	Package to collect result classes for the results of algorithms.
de.lmu.ifi.dbs.elki.algorithm.result.clustering	Package to collect result classes for the results of clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.result.clustering.biclustering	Package to collect result classes for the results of biclustering algorithms.
de.lmu.ifi.dbs.elki.data	Package collects basic classes for different data types, database object types and label types.
de.lmu.ifi.dbs.elki.database	Package collects variants of databases and related classes.
de.lmu.ifi.dbs.elki.database.connection	Provides database connection classes.
de.lmu.ifi.dbs.elki.distance	Package collects distances and - in its subpackages - distance and similarity functions.
de.lmu.ifi.dbs.elki.distance.distancefunction	Package collects distance functions.
de.lmu.ifi.dbs.elki.distance.similarityfunction	Package collects similarity functions.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Package collects kernel functions.
de.lmu.ifi.dbs.elki.index.tree	Package collects variants of tree-based index structures.
de.lmu.ifi.dbs.elki.index.tree.metrical	Package collects metrical tree-based index structures.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants	Package collects variants of the M-Tree.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkapp	Package collects classes for the MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkcop	Package collects classes for the MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkmax	Package collects classes for the MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktab	Package collects classes for the MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree	Package collects classes for the MTree
de.lmu.ifi.dbs.elki.index.tree.spatial	Package collects spatial tree-based index structures.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants	Package collects variants of the R*-Tree.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	Package collects classes for the DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn	Package collects classes for the RdKNNTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar	Package collects classes for the RStarTree
de.lmu.ifi.dbs.elki.logging	Logging facility for controlling logging behaviour of the complete framework.
de.lmu.ifi.dbs.elki.math.linearalgebra	Linear Algebra package provides classes and computational methods for operations on matrices.
de.lmu.ifi.dbs.elki.math.spacefillingcurves	Package to collect implementations of space filling curves.
de.lmu.ifi.dbs.elki.math.statistics	Package to support statistical tests and methods.
de.lmu.ifi.dbs.elki.normalization	Provides classes and methods for normalizations (and reconstitution) of data sets.
de.lmu.ifi.dbs.elki.parser	Package collects parser for different file formats and data types.
de.lmu.ifi.dbs.elki.persistent	Package collects classes for persistent data management.
de.lmu.ifi.dbs.elki.preprocessing	Package collects preprocessors used for data preparation in a first step of various algorithms or distance measures.
de.lmu.ifi.dbs.elki.properties	Contains the property-file and related classes for property handling.
de.lmu.ifi.dbs.elki.utilities	Package collects various classes and methods of global utility.
de.lmu.ifi.dbs.elki.utilities.heap	Package collects variants of heap structures.
de.lmu.ifi.dbs.elki.utilities.optionhandling	Package collects classes required for handling and description of options for any parameterizable class.
de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints	Constraints allow to restrict possible values for parameters.
de.lmu.ifi.dbs.elki.utilities.output	Helper-classes for output formatting.
de.lmu.ifi.dbs.elki.varianceanalysis	Classes for analysis of variance by different methods.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki

class

KDDTask<O extends DatabaseObject> Provides a KDDTask that can be used to perform any algorithm implementing Algorithm using any DatabaseConnection implementing DatabaseConnection.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm

class	AbstractAlgorithm<O extends DatabaseObject> AbstractAlgorithm sets the values for flags verbose and time.
class	APRIORI Provides the APRIORI algorithm for Mining Association Rules.
class	DependencyDerivator<V extends RealVector<V,?>,D extends Distance<D>> Dependency derivator computes quantitativly linear dependencies among attributes of a given dataset based on a linear correlation PCA.
class	DistanceBasedAlgorithm<O extends DatabaseObject,D extends Distance<D>> Provides an abstract algorithm already setting the distance function.
class	KNNDistanceOrder<O extends DatabaseObject,D extends Distance<D>> Provides an order of the kNN-distances for all objects within the database.
class	KNNJoin<V extends NumberVector<V,?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> Joins in a given spatial database to each object its k-nearest neighbors.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering

class	DBSCAN<O extends DatabaseObject,D extends Distance<D>> DBSCAN provides the DBSCAN algorithm, an algorithm to find density-connected sets in a database.
class	DeLiClu<O extends NumberVector<O,?>,D extends Distance<D>> DeLiClu provides the DeLiClu algorithm, a hierachical algorithm to find density-connected sets in a database.
class	EM<V extends RealVector<V,?>> Provides the EM algorithm (clustering by expectation maximization).
class	KMeans<D extends Distance<D>,V extends RealVector<V,?>> Provides the k-means algorithm.
class	OPTICS<O extends DatabaseObject,D extends Distance<D>> OPTICS provides the OPTICS algorithm.
class	ProjectedDBSCAN<V extends RealVector<V,?>> Provides an abstract algorithm requiring a VarianceAnalysisPreprocessor.
class	SLINK<O extends DatabaseObject,D extends Distance<D>> Efficient implementation of the Single-Link Algorithm SLINK of R.
class	SNNClustering<O extends DatabaseObject,D extends Distance<D>> Shared nearest neighbor clustering.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering

class

AbstractBiclustering<V extends RealVector<V,Double>> Abstract class as a convenience for different biclustering approaches.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

class	CASH Subspace clustering algorithm based on the hough transform.
class	COPAA<V extends RealVector<V,?>> Algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary algorithm over the partitions.
class	COPAC<V extends RealVector<V,?>> 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<V extends RealVector<V,?>> 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<O extends RealVector<O,?>> 4C identifies local subgroups of data objects sharing a uniform correlation.
class	ORCLUS<V extends RealVector<V,?>> ORCLUS provides the ORCLUS algorithm.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash

class	CASHInterval Provides a unique interval represented by its id, a hyper bounding box reppresenting the alpha intervals, an interval of the correspinding distance, and a set of objects ids associated with this interval.
class	CASHIntervalSplit Supports the splitting of CASH intervals.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

class	CLIQUE<V extends RealVector<V,?>> Implementation of the CLIQUE algorithm, a grid-based algorithm to identify dense clusters in subspaces of maximum dimensionality.
class	DiSH<V extends RealVector<V,?>> Algorithm for detecting subspace hierarchies.
class	PreDeCon<V extends RealVector<V,?>> PreDeCon computes clusters of subspace preference weighted connected points.
class	PROCLUS<V extends RealVector<V,?>> PROCLUS provides the PROCLUS algorithm.
class	ProjectedClustering<V extends RealVector<V,?>> Abstract superclass for PROCLUS and ORCLUS.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.result

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.result

class	AbstractResult<O extends DatabaseObject> Abstract super class for a result object.
class	AprioriResult Stores a apriori result.
class	CorrelationAnalysisSolution<V extends RealVector<V,?>> A solution of correlation analysis is a matrix of equations describing the dependencies.
class	KNNDistanceOrderResult<O extends DatabaseObject,D extends Distance<D>>
class	PartitionResults<O extends DatabaseObject> A result for a partitioning algorithm providing a single result for a single partition.
class	PointerRepresentation<O extends DatabaseObject,D extends Distance<D>> Provides the result of the single link algorithm SLINK.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.result.clustering

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.result.clustering

class	CASHResult TODO: comment
class	CLIQUEModel<V extends RealVector<V,?>> Represents a cluster model for a cluster in the CLIQUE algorithm.
class	Cluster<O extends DatabaseObject> todo arthur comment
class	ClusterOrder<O extends DatabaseObject,D extends Distance<D>> A class representing the cluster order of the OPTICS algorithm.
class	Clusters<O extends DatabaseObject> Provides a result of a clustering-algorithm that computes several clusters.
class	ClustersPlusNoise<O extends DatabaseObject> Provides a result of a clustering-algorithm that computes several clusters and remaining noise.
class	ClustersPlusNoisePlusCorrelationAnalysis<V extends RealVector<V,?>> Provides a result of a clustering-algorithm that computes several clusters and remaining noise and a correlation analysis for each cluster.
class	EMClusters<V extends RealVector<V,?>> // todo arthur comment
class	EMModel<V extends RealVector<V,?>> // todo arthur comment
class	HierarchicalAxesParallelCorrelationCluster Provides a hierarchical axes parallel correlation cluster that holds the preference vector of this cluster, the ids of the objects belonging to this cluster and the children and parents of this cluster.
class	HierarchicalAxesParallelCorrelationClusters<V extends RealVector<V,?>,D extends Distance<D>> Provides a result of a clustering algorithm that computes hierarchical axes parallel correlation clusters from a cluster order.
class	HierarchicalCASHCluster Provides a hierarchical correlation in an arbitrary subspace which is determined by the CASH algorithm that holds the interval of angles, the ids of the objects belonging to this cluster and the children and parents of this cluster.
class	HierarchicalCASHClusters Provides a result of the CASH clustering algorithm that computes hierarchical correlation clusters in arbitrary subspaces.
class	HierarchicalCluster<C extends HierarchicalCluster<C>> Abstract super class for a hierarchical cluster that holds the ids of the objects belonging to this cluster and the children and parents of this cluster.
class	HierarchicalClusters<C extends HierarchicalCluster<C>,O extends DatabaseObject> Provides a result of a clustering algorithm that computes hierarchical clusters.
class	HierarchicalCorrelationCluster<V extends RealVector<V,?>> Provides a hierarchical correlation cluster in an arbitrary subspace that holds the PCA, the ids of the objects belonging to this cluster and the children and parents of this cluster.
class	HierarchicalCorrelationClusters<V extends RealVector<V,?>> Provides a result of a clustering algorithm that computes hierarchical correlation clusters in arbitrary subspaces.
class	PartitionClusteringResults<O extends DatabaseObject> A result for a partitioning clustering algorithm providing a single result for a single partition.
class	SubspaceClusterModel<V extends RealVector<V,?>> todo arthur comment

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.result.clustering.biclustering

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.algorithm.result.clustering.biclustering

class	Bicluster<V extends RealVector<V,Double>> Wrapper class to provide the basic properties of a bicluster.
class	Biclustering<V extends RealVector<V,Double>> A Biclustering result holds a set of biclusters.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.data

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.data

class	AbstractDatabaseObject Abstract super class for all database objects.
class	BitVector Provides a BitVector wrapping a BitSet.
class	ClassLabel<L extends ClassLabel<L>> A ClassLabel to identify a certain class of objects that is to discern from other classes by a classifier.
class	DoubleVector A DoubleVector is to store real values approximately as double values.
class	ExternalObject Provides an id referencing an external data object.
class	FloatVector A FloatVector is to store real values approximately as float values.
class	HierarchicalClassLabel A HierarchicalClassLabel is a ClassLabel to reflect a hierarchical structure of classes.
class	MultiInstanceObject<O extends DatabaseObject> MultiInstanceObject represents a collection of several DatabaseObjects of an equal type.
class	MultiRepresentedObject<O extends DatabaseObject> MultiRepresentedObject represents a collection of several DatabaseObjects of a same superclass.
class	NumberVector<V extends NumberVector<V,N>,N extends Number> NumberVector is an abstract implementation of FeatureVector.
class	ParameterizationFunction A parameterization function decribes all lines in a d-dimensional feature space intersecting in one point p.
class	RealVector<V extends RealVector<V,N>,N extends Number> RealVector is an abstract super class for all feature vectors having real numbers as values.
class	SimpleClassLabel A simple class label casting a String as it is as label.
class	SparseDoubleVector A SparseDoubleVector is to store real values approximately as double values.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.database

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.database

class	AbstractDatabase<O extends DatabaseObject> Provides a mapping for associations based on a Hashtable and functions to get the next usable ID for insertion, making IDs reusable after deletion of the entry.
class	AssociationID<C> An AssociationID is used by databases as a unique identifier for specific associations to single objects.
class	AssociationMaps Helper class to facilitate an association mapping from AssociationID to a map from an object id to an associated object.
class	Associations A helper class to facilitate setting of global associations in a database.
class	IndexDatabase<O extends DatabaseObject> IndexDatabase is a database implementation which is supported by an index structure.
class	InvertedListDatabase<N extends Number,O extends FeatureVector<O,N>> Database implemented by inverted lists that supports range queries on a specific dimension.
class	MetricalIndexDatabase<O extends DatabaseObject,D extends Distance<D>,N extends MetricalNode<N,E>,E extends MTreeEntry<D>> MetricalIndexDatabase is a database implementation which is supported by a metrical index structure.
class	SequentialDatabase<O extends DatabaseObject> SequentialDatabase is a simple implementation of a Database.
class	SpatialIndexDatabase<O extends NumberVector<O,?>,N extends SpatialNode<N,E>,E extends SpatialEntry> SpatialIndexDatabase is a database implementation which is supported by a spatial index structure.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.database.connection

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.database.connection

class	AbstractDatabaseConnection<O extends DatabaseObject> Abstract super class for all database connections.
class	FileBasedDatabaseConnection<O extends DatabaseObject> Provides a file based database connection based on the parser to be set.
class	InputStreamDatabaseConnection<O extends DatabaseObject> Provides a database connection expecting input from standard in.
class	MultipleFileBasedDatabaseConnection<O extends DatabaseObject> Provides a database connection based on multiple files and parsers to be set.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance

(package private) class	AbstractDistance<D extends AbstractDistance<D>> An abstract distance implements equals conveniently for any extending class.
class	AbstractMeasurementFunction<O extends DatabaseObject,D extends Distance<D>> Abstract Measurement Function provides some methods valid for any extending class.
class	BitDistance TODO arthur comment
class	CorrelationDistance<D extends CorrelationDistance<D>> The CorrelationDistance is a special Distance that indicates the dissimilarity between correlation connected objects.
class	DoubleDistance Provides a Distance for a double-valued distance.
class	FloatDistance Provides a Distance for a float-valued distance.
class	IntegerDistance
class	NumberDistance<D extends NumberDistance<D>> Provides a Distance for a number-valued distance.
class	PreferenceVectorBasedCorrelationDistance A PreferenceVectorBasedCorrelationDistance holds additionally to the CorrelationDistance the common preference vector of the two objects defining the distance.
class	SubspaceDistance<D extends SubspaceDistance<D>> The SubspaceDistance is a special distance that indicates the dissimilarity between subspaces of equal dimensionality.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance.distancefunction

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance.distancefunction

class	AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>> Abstract super class for correlation based distance functions.
class	AbstractDimensionsSelectingDoubleDistanceFunction<V extends NumberVector<V,?>> Provides a distance function that computes the distance (which is a double distance) between feature vectors only in specified dimensions.
class	AbstractDistanceFunction<O extends DatabaseObject,D extends Distance<D>> AbstractDistanceFunction provides some methods valid for any extending class.
class	AbstractDoubleDistanceFunction<O extends DatabaseObject> Provides an abstract superclass for DistanceFunctions that are based on DoubleDistance.
class	AbstractFloatDistanceFunction<O extends DatabaseObject> Provides a DistanceFunction that is based on FloatDistance.
class	AbstractLocallyWeightedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Abstract super class for locally weighted distance functions using a preprocessor to compute the local weight matrix.
class	AbstractPreprocessorBasedDistanceFunction<O extends DatabaseObject,P extends Preprocessor<O>,D extends Distance<D>> Abstract super class for distance functions needing a preprocessor.
class	CosineDistanceFunction<V extends FeatureVector<V,?>> CosineDistanceFunction for FeatureVectors.
class	DimensionSelectingDistanceFunction<N extends Number,O extends FeatureVector<O,N>> Provides a distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension.
class	DimensionsSelectingEuklideanDistanceFunction<V extends NumberVector<V,?>> Provides a distance function that computes the Euklidean distance between feature vectors only in specified dimensions.
class	DirectSupportDependentItemsetDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	DiSHDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>> Distance function used in the DiSH algorithm.
class	ERiCDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>> Provides a distance function for building the hierarchiy in the ERiC algorithm.
class	EuklideanDistanceFunction<T extends NumberVector<T,?>> Provides the Euklidean distance for FeatureVectors.
class	FileBasedDoubleDistanceFunction Provides a DistanceFunction that is based on double distances given by a distance matrix of an external file.
class	FileBasedFloatDistanceFunction Provides a DistanceFunction that is based on float distances given by a distance matrix of an external file.
class	FractalDimensionBasedDistanceFunction<V extends RealVector<V,?>>
class	FrequencyDependentItemsetDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	HiSCDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Distance function used in the HiSC algorithm.
class	KernelBasedLocallyWeightedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Provides a kernel based locally weighted distance function.
class	LocallyWeightedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Provides a locally weighted distance function.
class	LPNormDistanceFunction<V extends FeatureVector<V,N>,N extends Number> Provides a LP-Norm for FeatureVectors.
class	ManhattanDistanceFunction<T extends NumberVector<T,?>> Manhattan distance function to compute the Manhattan distance for a pair of NumberVectors.
class	PCABasedCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>> Provides the Correlation distance for real valued vectors.
class	PreferenceVectorBasedCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> XXX unify CorrelationDistanceFunction and VarianceDistanceFunction
class	ReciprocalSupportDependentItemsetDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	RepresentationSelectingDistanceFunction<O extends DatabaseObject,M extends MultiRepresentedObject<O>,D extends Distance<D>> Distance function for multirepresented objects that selects one representation and computes the distances only within the selected representation.
class	SharedMaximumDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	SharedUnitedDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	SharingDependentItemsetDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	SquareRootSupportLengthDependentItemsetDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	SubspaceDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends SubspaceDistance<D>> Provides a distance function to determine a kind of correlation distance between two points, which is a pair consisting of the distance between the two subspaces spanned by the strong eigenvectors of the two points and the affine distance between the two subspaces.
class	SupportLengthDependentItemsetDistanceFunction Provides a DistanceFunction to compute a Distance between BitVectors based on the number of shared bits.
class	WeightedDistanceFunction<O extends NumberVector<O,?>> Provides the Weighted distance for feature vectors.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance.similarityfunction

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance.similarityfunction

class	AbstractIntegerSimilarityFunction<O extends DatabaseObject>
class	AbstractPreprocessorBasedSimilarityFunction<O extends DatabaseObject,P extends Preprocessor<O>,D extends Distance<D>> Abstract super class for distance functions needing a preprocessor.
class	AbstractSimilarityFunction<O extends DatabaseObject,D extends Distance<D>>
class	ClusterSimilarity
class	SharedNearestNeighborSimilarityFunction<O extends DatabaseObject,D extends Distance<D>>

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

class	AbstractDoubleKernelFunction<O extends DatabaseObject> Provides an abstract superclass for KernelFunctions that are based on DoubleDistance.
class	AbstractKernelFunction<O extends DatabaseObject,D extends Distance<D>> AbstractKernelFunction provides some methods valid for any extending class.
class	ArbitraryKernelFunctionWrapper<O extends RealVector<O,?>> Provides a wrapper for arbitrary kernel functions whose kernel matrix has been precomputed.
class	FooKernelFunction<O extends FeatureVector> Provides an experimental KernelDistanceFunction for RealVectors.
class	KernelMatrix<O extends RealVector<O,?>> Provides a class for storing the kernel matrix and several extraction methods for convenience.
class	LinearKernelFunction<O extends FeatureVector<O,?>> Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by V1^T*V2.
class	PolynomialKernelFunction<O extends FeatureVector<O,?>> Provides a polynomial Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by (V1^T*V2)^degree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree

class	AbstractNode<N extends AbstractNode<N,E>,E extends Entry> Abstract superclass for nodes in an tree based index structure.
class	TreeIndex<O extends DatabaseObject,N extends Node<N,E>,E extends Entry> Abstract super class for all tree based index classes.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical

class

MetricalIndex<O extends DatabaseObject,D extends Distance<D>,N extends MetricalNode<N,E>,E extends MetricalEntry> Abstract super class for all metrical index classes.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants

class	AbstractMTree<O extends DatabaseObject,D extends Distance<D>,N extends AbstractMTreeNode<O,D,N,E>,E extends MTreeEntry<D>> Abstract super class for all M-Tree variants.
class	AbstractMTreeNode<O extends DatabaseObject,D extends Distance<D>,N extends AbstractMTreeNode<O,D,N,E>,E extends MTreeEntry<D>> Represents a node in an AbstractM-Tree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkapp

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkapp

class	MkAppTree<O extends DatabaseObject,D extends NumberDistance<D>> MkAppTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
(package private) class	MkAppTreeNode<O extends DatabaseObject,D extends NumberDistance<D>> Represents a node in an MkApp-Tree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkcop

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkcop

class	MkCoPTree<O extends DatabaseObject,D extends NumberDistance<D>> MkCopTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
(package private) class	MkCoPTreeNode<O extends DatabaseObject,D extends NumberDistance<D>> Represents a node in an MkCop-Tree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkmax

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mkmax

class	MkMaxTree<O extends DatabaseObject,D extends Distance<D>> MkNNTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries.
(package private) class	MkMaxTreeNode<O extends DatabaseObject,D extends Distance<D>> Represents a node in a MkMax-Tree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktab

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktab

class	MkTabTree<O extends DatabaseObject,D extends Distance<D>> MkMaxTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
(package private) class	MkTabTreeNode<O extends DatabaseObject,D extends Distance<D>> Represents a node in a MkMax-Tree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree

class	MTree<O extends DatabaseObject,D extends Distance<D>> MTree is a metrical index structure based on the concepts of the M-Tree.
class	MTreeNode<O extends DatabaseObject,D extends Distance<D>> Represents a node in an M-Tree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial

class	BulkSplit Encapsulates the required parameters for a bulk split of a spatial index.
class	SpatialIndex<O extends NumberVector<O,?>,N extends SpatialNode<N,E>,E extends SpatialEntry> Abstract super class for all spatial index classes.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants

class	AbstractRStarTree<O extends NumberVector<O,?>,N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry> Abstract superclass for index structures based on a R*-Tree.
class	AbstractRStarTreeNode<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry> Abstract superclass for nodes in a R*-Tree.
class	NonFlatRStarTree<O extends NumberVector<O,?>,N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry> Abstract superclass for all non-flat R*-Tree variants.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu

class	DeLiCluNode Represents a node in a DeLiClu-Tree.
class	DeLiCluTree<O extends NumberVector<O,?>> DeLiCluTree is a spatial index structure based on an R-TRee.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn

class	RdKNNNode<D extends NumberDistance<D>> Represents a node in a RDkNN-Tree.
class	RdKNNTree<O extends NumberVector<O,?>,D extends NumberDistance<D>> RDkNNTree is a spatial index structure based on the concepts of the R*-Tree supporting efficient processing of reverse k nearest neighbor queries.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar

class	RStarTree<O extends NumberVector<O,?>> RStarTree is a spatial index structure based on the concepts of the R*-Tree.
class	RStarTreeNode Represents a node in an R*-Tree.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.logging

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.logging

class	DebugFilter A filter for all (or specified) logs - suitable for handling debugging messages.
class	ExceptionFilter A filter for exception logs - suitable for handling severe error messages.
class	InfoFilter A filter for info logs - suitable for handling verbose messages.
class	LoggingConfiguration Facility for configuration of logging.
class	MessageFilter A filter for message logs - suitable for handling messages.
class	ProgressFilter A filter for progress logs - suitable for handling progress messages.
class	SelectiveFilter A selective filter filters exactly for a certain LogLevel of LogRecords.
class	StaticLogger Subclass of AbstractLoggable , can be used in static environments.
class	WarningFilter A filter for warning logs - suitable for handling warning messages.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.math.linearalgebra

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.math.linearalgebra

class	LinearEquationSystem Class for systems of linear equations.
class	Matrix The Matrix Class represents real-valued matrices.
class	Vector Provides a vector object that encapsulates an m x 1 - matrix object.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.math.spacefillingcurves

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.math.spacefillingcurves

class

ZCurve Computes the z-values for specified double values.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.math.statistics

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.math.statistics

class	LinearRegression
class	MultipleLinearRegression Multiple linear regression attempts to model the relationship between two or more explanatory variables and a response variable by fitting a linear equation to observed data.
class	PolynomialRegression A polynomial fit is a specific type of multiple regression.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.normalization

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.normalization

class	AbstractNormalization<O extends DatabaseObject> Abstract super class for all normalizations.
class	AttributeWiseRealVectorNormalization<V extends RealVector<V,?>> Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.
class	DummyNormalization<O extends DatabaseObject> Dummy normalization that does nothing.
class	MultiRepresentedObjectNormalization<O extends DatabaseObject> Class to perform and undo a normalization on multi-represented objects with respect to given normalizations for each representation.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.parser

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.parser

class	AbstractParser<O extends DatabaseObject> Abstract superclass for all parsers providing the option handler for handling options.
class	BitVectorLabelParser Provides a parser for parsing one BitVector per line, bits separated by whitespace.
class	NumberDistanceParser<D extends NumberDistance<D>> Provides a parser for parsing one distance value per line.
class	ParameterizationFunctionLabelParser Provides a parser for parsing one point per line, attributes separated by whitespace.
class	RealVectorLabelParser<V extends RealVector<V,?>> Provides a parser for parsing one point per line, attributes separated by whitespace.
class	RealVectorLabelTransposingParser Parser reads points transposed.
class	SparseBitVectorLabelParser Provides a parser for parsing one sparse BitVector per line, where the indices of the one-bits are separated by whitespace.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.persistent

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.persistent

class	AbstractPage<P extends AbstractPage<P>> Abstract superclass for pages.
class	MemoryPageFile<P extends Page<P>> A memory based implementation of a PageFile that simulates I/O-access.
class	PageFile<P extends Page<P>> Abstract class implementing general methods of a PageFile.
class	PersistentPageFile<P extends Page<P>> A PersistentPageFile stores objects persistently that implement the Page interface.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.preprocessing

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.preprocessing

class	DiSHPreprocessor<V extends RealVector<V,N>,N extends Number> Preprocessor for DiSH preference vector assignment to objects of a certain database.
class	FourCPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Preprocessor for 4C local dimensionality and locally weighted matrix assignment to objects of a certain database.
class	FracClusPreprocessor<V extends RealVector<V,?>>
class	HiCOPreprocessor<V extends RealVector<V,?>> Abstract superclass for preprocessors for HiCO correlation dimension assignment to objects of a certain database.
class	HiSCPreprocessor<V extends RealVector<V,?>> Preprocessor for HiSC preference vector assignment to objects of a certain database.
class	KernelFourCPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Preprocessor for kernel 4C local dimensionality, neighbor objects and strong eigenvector matrix assignment to objects of a certain database.
class	KnnQueryBasedHiCOPreprocessor<V extends RealVector<V,?>> Computes the HiCO correlation dimension of objects of a certain database.
class	PreDeConPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Preprocessor for PreDeCon local dimensionality and locally weighted matrix assignment to objects of a certain database.
class	ProjectedDBSCANPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Abstract superclass for preprocessor of algorithms extending the ProjectedDBSCAN alghorithm.
class	RangeQueryBasedHiCOPreprocessor<V extends RealVector<V,?>> Computes the HiCO correlation dimension of objects of a certain database.
class	SharedNearestNeighborsPreprocessor<O extends DatabaseObject,D extends Distance<D>> A preprocessor for annotation of the ids of nearest neighbors to each database object.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.properties

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.properties

class	Properties Provides management of properties.
class	PropertyName todo: remove old property names?

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities

class	ConstantObject<D extends ConstantObject<D>> ConstantObject provides a parent class for constant objects, that are immutable and unique by class and name.
class	HyperBoundingBox HyperBoundingBox represents a hyperrectangle in the multidimensional space.
class	KNNList<D extends Distance<D>> A wrapper class for storing the k most similar comparable objects.
class	Util

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.heap

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.heap

class

PersistentHeap<K extends Comparable<K> & Serializable,V extends Identifiable & Serializable> Persistent implementation of a heap-based priority queue.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.optionhandling

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.optionhandling

class	AbstractParameterizable Abstract superclass for classes parameterizable.
class	ClassListParameter Parameter class for a parameter specifying a list of class names.
class	ClassParameter<C> Parameter class for a parameter specifying a class name.
class	DoubleListParameter Paramter class for a parameter specifying a list of double values.
class	DoubleParameter Parameter class for a parameter specifying a double value.
class	FileListParameter Parameter class for a parameter specifying a list of files.
class	FileParameter Parameter class for a parameter specifying a file.
class	Flag Option class specifying a flag object.
class	IntListParameter Paramter class for a parameter specifying a list of integer values.
class	IntParameter Parameter class for a parameter specifying an integer value.
class	ListParameter<T> Abstract parameter class defining a parameter for a list of objects.
class	LongParameter Parameter class for a parameter specifying a long value.
class	NumberParameter<T extends Number> Abstract class for defining a number parameter.
class	Option<T> Abstract superclass for specifying program arguments.
class	OptionHandler Provides an OptionHandler for holding the given options.
class	OptionID An OptionID is used by option handlers as a unique identifier for specific options.
class	Parameter<T,C> Abstract class for specifying a parameter.
class	PatternParameter Parameter class for a parameter specifying a pattern.
class	StringParameter Parameter class for a parameter specifying a string value.
class	VectorListParameter Parameter class for a parameter specifying a list of vectors.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints

class	AbstractNumberConstraint<P> Abstract super class for constraints dealing with a certain number value.
class	AllOrNoneMustBeSetGlobalConstraint Global parameter constraint specifying that either all elements of a list of parameters (Parameter) must be set, or none of them.
class	DefaultValueGlobalConstraint<T extends Comparable<T>> Global parameter constraint for specifying the default value of a parameter dependent on the parameter value of another parameter.
class	DistanceFunctionPatternConstraint Parameter constraint class for testing if a given pattern parameter (PatternParameter) holds a valid pattern for a specific distance function (DistanceFunction).
class	EqualSizeGlobalConstraint Global parameter constraint defining that a number of list parameters (ListParameter) must have equal list sizes.
class	EqualStringConstraint Represents a parameter constraint for testing if the string value of the string parameter (StringParameter) to be tested is equal to the specified constraint-strings.
class	GlobalDistanceFunctionPatternConstraint<D extends DistanceFunction<?,?>> Global parameter constraint for testing if a given pattern parameter (PatternParameter) specifies a valid pattern for a given class parameter (ClassParameter) defining a specific distance function.
class	GlobalListSizeConstraint Represents a global parameter constraint for testing if the size of the list parameter (ListParameter) given is equal to the constraint size specified by the integer parameter (IntParameter) given.
class	GlobalVectorListElementSizeConstraint Global parameter constraint for testing if the dimensions of each vector specified by a given vector list parameter (VectorListParameter) correspond to the value of a integer parameter (IntParameter) given.
class	GreaterConstraint Represents a parameter constraint for testing if the value of the number parameter (NumberParameter) tested is greater than the specified constraint value.
class	GreaterEqualConstraint Represents a Greater-Equal-Than-Number parameter constraint.
class	IntervalConstraint Represents an interval parameter constraint testing if a given value lies within the specified interval.
class	LessConstraint Represents a Less-Than-Number parameter constraint.
class	LessEqualConstraint Represents a Less-Equal-Than-Number parameter constraint.
class	LessEqualGlobalConstraint<T extends Number> Represents a Less-Equal-Than global parameter constraint.
class	LessGlobalConstraint<T extends Number> Represents a Less-Than global parameter constraint.
class	ListGreaterEqualConstraint<N extends Number> Represents a Greater-Equal-Than-Number parameter constraint for a list of number values.
class	ListSizeConstraint<T> Represents a list-size parameter constraint.
class	NotEqualValueGlobalConstraint<N extends Number> Global parameter constraint specifying that parameters of a list of number parameters (NumberParameter) are not allowed to have the same value.
class	OneMustBeSetGlobalConstraint Represents a global parameter constraint specifying that at least one parameter value of a given list of parameters (Parameter) has to be set.
class	OnlyOneIsAllowedToBeSetGlobalConstraint Global parameter constraint specifying that only one parameter of a list of parameters (Parameter) is allowed to be set.
class	ParameterFlagGlobalConstraint<C,T extends C> Global parameter constraint describing the dependency of a parameter (Parameter) on a given flag (Flag).

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.output

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.utilities.output

class

PrettyPrinter Class for formatting output into table.

Uses of AbstractLoggable in de.lmu.ifi.dbs.elki.varianceanalysis

Subclasses of AbstractLoggable in de.lmu.ifi.dbs.elki.varianceanalysis

class	AbstractPCA Abstract super class for pca algorithms.
class	CompositeEigenPairFilter The CompositeEigenPairFilter can be used to build a chain of eigenpair filters.
class	FirstNEigenPairFilter The FirstNEigenPairFilter marks the n highest eigenpairs as strong eigenpairs, where n is a user specified number.
class	GlobalPCA<O extends RealVector<O,?>> Computes the principal components for vector objects of a given database.
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	LinearLocalPCA<V extends RealVector<V,?>> Performs a linear local PCA based on the covariance matrices of given objects.
class	LocalKernelPCA<V extends RealVector<V,?>> Performs a local kernel PCA based on the kernel matrices of given objects.
class	LocalPCA<V extends RealVector<V,?>> LocalPCA is a super calss for PCA-algorithms considering only a local neighborhood.
class	NormalizingEigenPairFilter The NormalizingEigenPairFilter normalizes all eigenvectors s.t.
class	PercentageEigenPairFilter The PercentageEigenPairFilter sorts the eigenpairs in decending 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.