Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm |
Algorithms suitable as a task for the
KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.benchmark |
Benchmarking pseudo algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.classification |
Classification algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering |
Clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation |
Affinity Propagation (AP) clustering.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering |
Biclustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash |
Helper classes for the
CASH algorithm. |
de.lmu.ifi.dbs.elki.algorithm.clustering.em |
Expectation-Maximization clustering algorithm.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction |
Extraction of partitional clusterings from hierarchical results.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization |
Initialization strategies for k-means.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel |
Parallelized implementations of k-means.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality |
Quality measures for k-Means results.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.meta |
Meta clustering algorithms, that get their result from other clusterings or external sources.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional |
Clustering algorithms for one-dimensional data.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.optics |
OPTICS family of clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique |
Helper classes for the
CLIQUE algorithm. |
de.lmu.ifi.dbs.elki.algorithm.clustering.trivial |
Trivial clustering algorithms: all in one, no clusters, label clusterings
These methods are mostly useful for providing a reference result in evaluation.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain |
Clustering algorithms for uncertain data.
|
de.lmu.ifi.dbs.elki.algorithm.itemsetmining |
Algorithms for frequent itemset mining such as APRIORI.
|
de.lmu.ifi.dbs.elki.algorithm.outlier |
Outlier detection algorithms
|
de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased |
Angle-based outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.clustering |
Clustering based outlier detection.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.distance |
Distance-based outlier detection algorithms, such as DBOutlier and kNN.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.lof |
LOF family of outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.meta |
Meta outlier detection algorithms: external scores, score rescaling.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial |
Spatial outlier detection algorithms
|
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.svm |
Support-Vector-Machines for outlier detection.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.trivial |
Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms.
|
de.lmu.ifi.dbs.elki.application.greedyensemble |
Greedy ensembles for outlier detection.
|
de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types.
|
de.lmu.ifi.dbs.elki.data.model |
Cluster models classes for various algorithms.
|
de.lmu.ifi.dbs.elki.data.projection |
Data projections.
|
de.lmu.ifi.dbs.elki.data.spatial |
Spatial data types - interfaces and utilities.
|
de.lmu.ifi.dbs.elki.data.synthetic.bymodel |
Generator using a distribution model specified in an XML configuration file.
|
de.lmu.ifi.dbs.elki.data.type |
Data type information, also used for type restrictions.
|
de.lmu.ifi.dbs.elki.data.uncertain |
Uncertain data objects.
|
de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier |
Classes to generate uncertain objects from existing certain data.
|
de.lmu.ifi.dbs.elki.database.query.knn |
Prepared queries for k nearest neighbor (kNN) queries.
|
de.lmu.ifi.dbs.elki.database.query.range |
Prepared queries for ε-range queries, that return all objects within the radius ε.
|
de.lmu.ifi.dbs.elki.database.relation |
Relations, materialized and virtual (views).
|
de.lmu.ifi.dbs.elki.datasource.filter |
Data filtering, in particular for normalization and projection.
|
de.lmu.ifi.dbs.elki.datasource.filter.cleaning |
Filters for data cleaning.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization |
Data normalization.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise |
Normalizations operating on columns / variates; where each column is treated independently.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise |
Instancewise normalization, where each instance is normalized independently.
|
de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations.
|
de.lmu.ifi.dbs.elki.datasource.filter.typeconversions |
Filters to perform data type conversions.
|
de.lmu.ifi.dbs.elki.datasource.parser |
Parsers for different file formats and data types.
|
de.lmu.ifi.dbs.elki.distance.distancefunction |
Distance functions for use within ELKI.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram |
Distance functions using correlations.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation |
Distance functions using correlations.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.geo |
Geographic (earth) distance functions.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.histogram |
Distance functions for one-dimensional histograms.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski |
Minkowski space L_p norms such as the popular Euclidean and Manhattan distances.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic |
Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.set |
Distance functions for binary and set type data.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace |
Distance functions based on subspaces.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries |
Distance functions designed for time series.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction |
Similarity functions.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster |
Similarity measures for comparing clusters.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel |
Kernel functions.
|
de.lmu.ifi.dbs.elki.evaluation.classification |
Evaluation of classification algorithms.
|
de.lmu.ifi.dbs.elki.evaluation.classification.holdout |
Holdout and cross-validation strategies for evaluating classifiers.
|
de.lmu.ifi.dbs.elki.evaluation.clustering |
Evaluation of clustering results.
|
de.lmu.ifi.dbs.elki.evaluation.clustering.internal |
Internal evaluation measures for clusterings.
|
de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments |
Pair-segment analysis of multiple clusterings.
|
de.lmu.ifi.dbs.elki.evaluation.histogram |
Functionality for the evaluation of algorithms using histograms.
|
de.lmu.ifi.dbs.elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
|
de.lmu.ifi.dbs.elki.evaluation.scores |
Evaluation of rankings and scorings.
|
de.lmu.ifi.dbs.elki.evaluation.scores.adapter |
Adapter classes for ranking and scoring measures.
|
de.lmu.ifi.dbs.elki.index.invertedlist |
Indexes using inverted lists.
|
de.lmu.ifi.dbs.elki.index.lsh.hashfamilies |
Hash function families for LSH.
|
de.lmu.ifi.dbs.elki.index.lsh.hashfunctions |
Hash functions for LSH
|
de.lmu.ifi.dbs.elki.index.preprocessed |
Index structure based on preprocessors
|
de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics |
Preprocessed index used by the FastOPTICS algorithm.
|
de.lmu.ifi.dbs.elki.index.preprocessed.knn |
Indexes providing KNN and rKNN data.
|
de.lmu.ifi.dbs.elki.index.preprocessed.localpca |
Index using a preprocessed local PCA.
|
de.lmu.ifi.dbs.elki.index.preprocessed.preference |
Indexes storing preference vectors.
|
de.lmu.ifi.dbs.elki.index.projected |
Projected indexes for data.
|
de.lmu.ifi.dbs.elki.index.tree.spatial |
Tree-based index structures for spatial indexing.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.kd |
K-d-tree and variants.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants |
R*-Tree and variants.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu | |
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat | |
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query |
Queries on the R-Tree family of indexes: kNN and range queries.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn | |
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar | |
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split |
Splitting strategies for R-Trees
|
de.lmu.ifi.dbs.elki.index.vafile |
Vector Approximation File
|
de.lmu.ifi.dbs.elki.math |
Mathematical operations and utilities used throughout the framework.
|
de.lmu.ifi.dbs.elki.math.dimensionsimilarity |
Functions to compute the similarity of dimensions (or the interestingness of the combination).
|
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.linearalgebra.pca |
Principal Component Analysis (PCA) and Eigenvector processing.
|
de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections |
Random projection families.
|
de.lmu.ifi.dbs.elki.math.spacefillingcurves |
Space filling curves.
|
de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
de.lmu.ifi.dbs.elki.result.textwriter |
Text serialization (CSV, Gnuplot, Console, ...)
|
de.lmu.ifi.dbs.elki.result.textwriter.naming |
Naming schemes for clusters (for output when an algorithm doesn't generate cluster names).
|
de.lmu.ifi.dbs.elki.utilities |
Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
|
de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike |
Common API for accessing objects that are "array-like", including lists, numerical vectors, database vectors and arrays.
|
de.lmu.ifi.dbs.elki.utilities.referencepoints |
Package containing strategies to obtain reference points
Shared code for various algorithms that use reference points.
|
de.lmu.ifi.dbs.elki.visualization |
Visualization package of ELKI.
|
de.lmu.ifi.dbs.elki.visualization.gui |
Package to provide a visualization GUI.
|
de.lmu.ifi.dbs.elki.visualization.opticsplot |
Code for drawing OPTICS plots
|
de.lmu.ifi.dbs.elki.visualization.projections |
Visualization projections
|
de.lmu.ifi.dbs.elki.visualization.projector |
Projectors are responsible for finding appropriate projections for data relations.
|
de.lmu.ifi.dbs.elki.visualization.style |
Style management for ELKI visualizations.
|
de.lmu.ifi.dbs.elki.visualization.svg |
Base SVG functionality (generation, markers, thumbnails, export, ...).
|
de.lmu.ifi.dbs.elki.visualization.visualizers.actions |
Action-only "visualizers" that only produce menu entries.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.histogram |
Visualizers based on 1D projected histograms.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.optics |
Visualizers that do work on OPTICS plots
|
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection |
Visualizers for object selection based on parallel projections.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot |
Visualizers based on scatterplots.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster |
Visualizers for clustering results based on 2D projections.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection |
Visualizers for object selection based on 2D projections.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj |
Visualizers that do not use a particular projection.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
HyperBoundingBox
HyperBoundingBox represents a hyperrectangle in the multidimensional space.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Subspace
Represents a subspace of the original data space.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Subspace
Represents a subspace of the original data space.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
DoubleVector
Vector type using
double[] storage for real numbers. |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
BitVector
Vector using a dense bit set encoding, based on
long[] storage. |
SparseFeatureVector
Extended interface for sparse feature vector types.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
DoubleVector
Vector type using
double[] storage for real numbers. |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
AbstractNumberVector
AbstractNumberVector is an abstract implementation of FeatureVector.
|
AbstractNumberVector.Factory
Factory class.
|
Bit
A boolean number type.
|
BitVector
Vector using a dense bit set encoding, based on
long[] storage. |
BitVector.Factory
Factory for bit vectors.
|
ByteVector
Vector using
byte[] storage. |
ByteVector.Factory
Factory for Byte vectors.
|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
ClassLabel.Factory
Class label factory.
|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
DoubleVector
Vector type using
double[] storage for real numbers. |
DoubleVector.Factory
Factory for Double vectors.
|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
FeatureVector.Factory
Factory API for this feature vector.
|
FloatVector
Vector type using
float[] storage, thus needing approximately half as
much memory as DoubleVector . |
FloatVector.Factory
Factory for float vectors.
|
HierarchicalClassLabel
A HierarchicalClassLabel is a ClassLabel to reflect a hierarchical structure
of classes.
|
HyperBoundingBox
HyperBoundingBox represents a hyperrectangle in the multidimensional space.
|
IntegerVector
Vector type using
int[] storage. |
IntegerVector.Factory
Factory for integer vectors.
|
LabelList
A list of string labels.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
OneDimensionalDoubleVector
Specialized class implementing a one-dimensional double vector without using
an array.
|
OneDimensionalDoubleVector.Factory
Factory class.
|
ShortVector
Vector type using
short[] storage. |
ShortVector.Factory
Factory for Short vectors.
|
SimpleClassLabel
A simple class label casting a String as it is as label.
|
SparseByteVector
Sparse vector type, using
byte[] for storing the values, and
int[] for storing the indexes, approximately 5 bytes per non-zero
value (limited to -128..+127). |
SparseByteVector.Factory
Factory class.
|
SparseDoubleVector
Sparse vector type, using
double[] for storing the values, and
int[] for storing the indexes, approximately 12 bytes per non-zero
value. |
SparseDoubleVector.Factory
Factory class.
|
SparseFeatureVector
Extended interface for sparse feature vector types.
|
SparseFloatVector
Sparse vector type, using
float[] for storing the values, and
int[] for storing the indexes, approximately 8 bytes per non-zero
value. |
SparseFloatVector.Factory
Factory class.
|
SparseIntegerVector
Sparse vector type, using
int[] for storing the values, and
int[] for storing the indexes, approximately 8 bytes per non-zero
integer value. |
SparseIntegerVector.Factory
Factory class.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
SparseNumberVector.Factory
Factory for sparse number vectors: make from a dim-value map.
|
SparseShortVector
Sparse vector type, using
short[] for storing the values, and
int[] for storing the indexes, approximately 6 bytes per non-zero
value. |
SparseShortVector.Factory
Factory class.
|
Subspace
Represents a subspace of the original data space.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Subspace
Represents a subspace of the original data space.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
FeatureVector.Factory
Factory API for this feature vector.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
Class and Description |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
Class and Description |
---|
BitVector
Vector using a dense bit set encoding, based on
long[] storage. |
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
Clustering
Result class for clusterings.
|
DoubleVector
Vector type using
double[] storage for real numbers. |
ExternalID
External ID objects.
|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
FeatureVector.Factory
Factory API for this feature vector.
|
FloatVector
Vector type using
float[] storage, thus needing approximately half as
much memory as DoubleVector . |
LabelList
A list of string labels.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
SimpleClassLabel
A simple class label casting a String as it is as label.
|
SparseDoubleVector
Sparse vector type, using
double[] for storing the values, and
int[] for storing the indexes, approximately 12 bytes per non-zero
value. |
SparseFloatVector
Sparse vector type, using
float[] for storing the values, and
int[] for storing the indexes, approximately 8 bytes per non-zero
value. |
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Class and Description |
---|
DoubleVector
Vector type using
double[] storage for real numbers. |
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
FeatureVector.Factory
Factory API for this feature vector.
|
HyperBoundingBox
HyperBoundingBox represents a hyperrectangle in the multidimensional space.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
DoubleVector
Vector type using
double[] storage for real numbers. |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
ClassLabel.Factory
Class label factory.
|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
SimpleClassLabel
A simple class label casting a String as it is as label.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Class and Description |
---|
BitVector
Vector using a dense bit set encoding, based on
long[] storage. |
Clustering
Result class for clusterings.
|
ExternalID
External ID objects.
|
LabelList
A list of string labels.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
SparseNumberVector.Factory
Factory for sparse number vectors: make from a dim-value map.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
Class and Description |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Class and Description |
---|
DoubleVector
Vector type using
double[] storage for real numbers. |
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
VectorUtil.SortDBIDsBySingleDimension
Compare number vectors by a single dimension.
|
Class and Description |
---|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
FeatureVector.Factory
Factory API for this feature vector.
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
BitVector
Vector using a dense bit set encoding, based on
long[] storage. |
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Class and Description |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
Class and Description |
---|
FeatureVector
Generic FeatureVector class that can contain any type of data (i.e. numerical
or categorical attributes).
|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
NumberVector.Factory
Factory API for this feature vector.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Clustering
Result class for clusterings.
|
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Class and Description |
---|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
Class and Description |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Class and Description |
---|
ModifiableHyperBoundingBox
MBR class allowing modifications (as opposed to
HyperBoundingBox ). |
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Class and Description |
---|
Cluster
Generic cluster class, that may or not have hierarchical information.
|
Clustering
Result class for clusterings.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.