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
Clustering algorithms are supposed to implement the
Algorithm -Interface. |
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
Generalized DBSCAN is an abstraction of the original DBSCAN idea,
that allows the use of arbitrary "neighborhood" and "core point" predicates.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel |
Parallel versions of Generalized DBSCAN.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch |
BIRCH clustering.
|
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
The clustering algorithms in this package are instances of both, projected
clustering algorithms or subspace clustering algorithms according to the
classical but somewhat obsolete classification schema of clustering
algorithms for axis-parallel subspaces.
|
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.itemsetmining.associationrules |
Association rule mining.
|
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
Methods that detect outliers in subspaces (projections) of the data set.
|
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.projection |
Data projections (see also preprocessing filters for basic projections).
|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.timeseries |
Algorithms for change point detection in time series.
|
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.projection.random |
Random projection families
|
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
GeneratorXMLSpec is a standalone
application that loads an XML specification file and generates a synthetic
data set according to the specifications given. |
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 |
ELKI database layer - loading, storing, indexing and accessing 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.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
The general use-case for any parser is to create objects out of an
InputStream (e.g. by reading a data file). |
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 Lp 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, F-divergence, χ²-divergence, etc.
|
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
Note that some regular distance functions (e.g., Euclidean) are also used on
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.outlier |
Evaluate an outlier score using a misclassification based cost model
|
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.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.linearalgebra |
The linear algebra package provides classes and computational methods for
operations on matrices and vectors.
|
de.lmu.ifi.dbs.elki.math.linearalgebra.pca |
Principal Component Analysis (PCA) and Eigenvector processing
|
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.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.parallel3d |
3DPC: 3D parallel coordinate plot visualization for ELKI.
|
de.lmu.ifi.dbs.elki.visualization.parallel3d.layout |
Layouting algorithms for 3D parallel coordinate 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
|
tutorial.clustering |
Classes from the tutorial on implementing a custom k-means variation
|
tutorial.distancefunction |
Classes from the tutorial on implementing distance functions
|
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.
|
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 |
---|
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 |
---|
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.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
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.
|
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.
|
SparseNumberVector
Combines the SparseFeatureVector and NumberVector.
|
Class and Description |
---|
BitVector
Vector using a dense bit set encoding, based on
long[] storage. |
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.
|
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.
|
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. |
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 |
---|
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.
|
Clustering
Result class for clusterings.
|
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 |
---|
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 |
---|
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 |
---|
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.
|
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 |
---|
ClassLabel
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
|
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.
|
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 |
---|
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.
|
Clustering
Result class for clusterings.
|
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 |
---|
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 |
---|
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 |
---|
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 |
---|
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 |
---|
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.
|
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.
|
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.
|
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 |
---|
NumberVector
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
|
Copyright © 2019 ELKI Development Team. License information.