Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm |
Algorithms suitable as a task for the
KDDTask main routine. |
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.em |
Expectation-Maximization clustering algorithm.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical |
Hierarchical agglomerative clustering (HAC).
|
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.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.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.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.distance.parallel |
Parallel implementations of distance-based outlier detectors.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.lof |
LOF family of outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.lof.parallel |
Parallelized variants of LOF.
|
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.statistics |
Statistical analysis algorithms
The algorithms in this package perform statistical analysis of the data
(e.g. compute distributions, distance distributions etc.)
|
de.lmu.ifi.dbs.elki.application |
Base classes for stand alone applications.
|
de.lmu.ifi.dbs.elki.application.greedyensemble |
Greedy ensembles for outlier detection.
|
de.lmu.ifi.dbs.elki.application.internal |
Internal utilities for development.
|
de.lmu.ifi.dbs.elki.data.uncertain |
Uncertain data objects.
|
de.lmu.ifi.dbs.elki.database |
ELKI database layer - loading, storing, indexing and accessing data
|
de.lmu.ifi.dbs.elki.database.ids.integer |
Integer-based DBID implementation --
do not use directly - always use
DBIDUtil . |
de.lmu.ifi.dbs.elki.datasource |
Data normalization (and reconstitution) of data sets.
|
de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations.
|
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.external |
Distance functions using external data sources.
|
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.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.strings |
Distance functions for strings.
|
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.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.index.idistance |
iDistance is a distance based indexing technique, using a reference points embedding.
|
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.preprocessed.snn |
Indexes providing nearest neighbor sets
|
de.lmu.ifi.dbs.elki.index.projected |
Projected indexes for data.
|
de.lmu.ifi.dbs.elki.index.tree.metrical.covertree |
Cover-tree variations.
|
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree | |
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.insert |
Insertion (choose path) strategies of nodes in an M-Tree (and variants).
|
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split |
Splitting strategies of nodes in an M-Tree (and variants).
|
de.lmu.ifi.dbs.elki.index.tree.spatial.kd |
K-d-tree and variants.
|
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.rstar | |
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk |
Packages for bulk-loading R*-Trees.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert |
Insertion strategies for R-Trees
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.overflow |
Overflow treatment strategies for R-Trees
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert |
Reinsertion strategies for R-Trees
|
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.geodesy | |
de.lmu.ifi.dbs.elki.math.geometry |
Algorithms from computational geometry.
|
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.random |
Random number generation.
|
de.lmu.ifi.dbs.elki.math.spacefillingcurves |
Space filling curves.
|
de.lmu.ifi.dbs.elki.math.statistics |
Statistical tests and methods.
|
de.lmu.ifi.dbs.elki.math.statistics.dependence |
Statistical measures of dependence, such as correlation.
|
de.lmu.ifi.dbs.elki.math.statistics.distribution |
Standard distributions, with random generation functionalities.
|
de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator |
Estimators for statistical distributions.
|
de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta |
Meta estimators: estimators that do not actually estimate themselves, but instead use other estimators, e.g. on a trimmed data set, or as an ensemble.
|
de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality |
Methods for estimating the intrinsic dimensionality.
|
de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions |
Kernel functions from statistics.
|
de.lmu.ifi.dbs.elki.math.statistics.tests |
Statistical tests.
|
de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
de.lmu.ifi.dbs.elki.utilities.datastructures.arrays |
Utilities for arrays: advanced sorting for primitvie arrays.
|
de.lmu.ifi.dbs.elki.utilities.documentation |
Documentation utilities: Annotations for Title, Description, Reference
|
de.lmu.ifi.dbs.elki.utilities.scaling.outlier |
Scaling of Outlier scores, that require a statistical analysis of the occurring values
|
de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments |
Visualizers for inspecting cluster differences using pair counting segments.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density |
Visualizers for data set density in a scatterplot projection.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier |
Visualizers for outlier scores based on 2D projections.
|
tutorial.clustering |
Classes from the tutorial on implementing a custom k-means variation.
|
tutorial.outlier |
Class and Description |
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Description
Class/algorithm description
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Reference
Annotation to specify a reference.
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Title
Simple interface to provide a nicer title for the class.
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Description
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Title
Simple interface to provide a nicer title for the class.
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Class/algorithm description
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Annotation to specify a reference.
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Title
Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Title
Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Class/algorithm description
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Title
Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Class/algorithm description
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Class/algorithm description
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Annotation to specify a reference.
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Title
Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Title
Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Annotation to specify a reference.
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Simple interface to provide a nicer title for the class.
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Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.