| elki |
ELKI framework "Environment for Developing KDD-Applications Supported by
Index-Structures".
|
| elki.algorithm |
Miscellaneous algorithms.
|
| elki.algorithm.statistics |
Statistical analysis algorithms.
|
| elki.application |
Base classes for standalone applications.
|
| elki.application.benchmark |
Benchmarking pseudo algorithms.
|
| elki.application.cache |
Utility applications for the persistence layer such as distance cache
builders.
|
| elki.application.experiments |
Packaged experiments to make them easy to reproduce.
|
| elki.application.greedyensemble |
Greedy ensembles for outlier detection.
|
| elki.application.internal |
Internal utilities for development.
|
| elki.application.statistics |
Applications to compute some basic data set statistics.
|
| elki.classification |
Classification algorithms.
|
| elki.clustering |
Clustering algorithms.
|
| elki.clustering.affinitypropagation |
Affinity Propagation (AP) clustering.
|
| elki.clustering.biclustering |
Biclustering algorithms.
|
| elki.clustering.correlation |
Correlation clustering algorithms.
|
| elki.clustering.correlation.cash |
Helper classes for the
CASH
algorithm. |
| elki.clustering.dbscan |
DBSCAN and its generalizations.
|
| elki.clustering.dbscan.parallel |
Parallel versions of Generalized DBSCAN.
|
| elki.clustering.dbscan.predicates |
Neighbor and core predicated for Generalized DBSCAN.
|
| elki.clustering.dbscan.util |
Utility classes for specialized DBSCAN implementations.
|
| elki.clustering.em |
Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling
(GMM).
|
| elki.clustering.em.models |
|
| elki.clustering.hierarchical |
Hierarchical agglomerative clustering (HAC).
|
| elki.clustering.hierarchical.birch |
BIRCH clustering.
|
| elki.clustering.hierarchical.extraction |
Extraction of partitional clusterings from hierarchical results.
|
| elki.clustering.hierarchical.linkage |
Linkages for hierarchical clustering.
|
| elki.clustering.kcenter |
K-center clustering.
|
| elki.clustering.kmeans |
K-means clustering and variations.
|
| elki.clustering.kmeans.initialization |
Initialization strategies for k-means.
|
| elki.clustering.kmeans.initialization.betula |
Initialization methods for BIRCH-based k-means and EM clustering.
|
| elki.clustering.kmeans.parallel |
Parallelized implementations of k-means.
|
| elki.clustering.kmeans.quality |
Quality measures for k-Means results.
|
| elki.clustering.kmeans.spherical |
Spherical k-means clustering and variations.
|
| elki.clustering.kmedoids |
K-medoids clustering (PAM).
|
| elki.clustering.kmedoids.initialization |
|
| elki.clustering.meta |
Meta clustering algorithms, that get their result from other clusterings or
external sources.
|
| elki.clustering.onedimensional |
Clustering algorithms for one-dimensional data.
|
| elki.clustering.optics |
OPTICS family of clustering algorithms.
|
| elki.clustering.silhouette |
Silhouette clustering algorithms.
|
| elki.clustering.subspace |
Axis-parallel subspace clustering algorithms.
|
| elki.clustering.subspace.clique |
Helper classes for the
CLIQUE
algorithm. |
| elki.clustering.svm |
|
| elki.clustering.trivial |
Trivial clustering algorithms: all in one, no clusters, label clusterings.
|
| elki.clustering.uncertain |
Clustering algorithms for uncertain data.
|
| elki.data |
Basic classes for different data types, database object types and label types.
|
| elki.data.model |
Cluster models classes for various algorithms.
|
| elki.data.projection |
Data projections.
|
| elki.data.projection.random |
Random projection families.
|
| elki.data.spatial |
Spatial data types - interfaces and utilities.
|
| elki.data.synthetic.bymodel |
Generator using a distribution model specified in an XML configuration file.
|
| elki.data.type |
Data type information, also used for type restrictions.
|
| elki.data.uncertain |
Uncertain data objects.
|
| elki.data.uncertain.uncertainifier |
Classes to generate uncertain objects from existing certain data.
|
| elki.database |
ELKI database layer - loading, storing, indexing and accessing data.
|
| elki.database.datastore |
General data store layer API (along the lines of
Map<DBID, T> - use everywhere!)
|
| elki.database.datastore.memory |
Memory data store implementation for ELKI.
|
| elki.database.ids |
Database object identification and ID group handling API.
|
| elki.database.ids.integer |
Integer-based DBID implementation --
do not use directly - always use DBIDUtil. |
| elki.database.query |
Database queries - computing distances, neighbors, similarities - API
and general documentation.
|
| elki.database.query.distance |
Prepared queries for distances.
|
| elki.database.query.knn |
Prepared queries for k nearest neighbor (kNN) queries.
|
| elki.database.query.range |
Prepared queries for ε-range queries, that return all objects within
the radius ε.
|
| elki.database.query.rknn |
Prepared queries for reverse k nearest neighbor (rkNN) queries.
|
| elki.database.query.similarity |
Prepared queries for similarity functions.
|
| elki.database.relation |
Relations, materialized and virtual (views).
|
| elki.datasource |
Data normalization (and reconstitution) of data sets.
|
| elki.datasource.bundle |
Object bundles - exchange container for multi-represented objects.
|
| elki.datasource.filter |
Data filtering, in particular for normalization and projection.
|
| elki.datasource.filter.cleaning |
Filters for data cleaning.
|
| elki.datasource.filter.normalization |
Data normalization.
|
| elki.datasource.filter.normalization.columnwise |
Normalizations operating on columns / variates; where each column is treated independently.
|
| elki.datasource.filter.normalization.instancewise |
Instancewise normalization, where each instance is normalized independently.
|
| elki.datasource.filter.selection |
Filters for selecting and sorting data to process.
|
| elki.datasource.filter.transform |
Data space transformations.
|
| elki.datasource.filter.typeconversions |
Filters to perform data type conversions.
|
| elki.datasource.parser |
Parsers for different file formats and data types.
|
| elki.distance |
Distance functions for use within ELKI.
|
| elki.distance.adapter |
Distance functions deriving distances from, e.g., similarity measures.
|
| elki.distance.colorhistogram |
Distance functions for color histograms.
|
| elki.distance.correlation |
Distance functions using correlations.
|
| elki.distance.external |
Distance functions using external data sources.
|
| elki.distance.geo |
Geographic (earth) distance functions.
|
| elki.distance.histogram |
Distance functions for one-dimensional histograms.
|
| elki.distance.minkowski |
Minkowski space Lp norms such as the popular Euclidean and
Manhattan distances.
|
| elki.distance.probabilistic |
Distance from probability theory, mostly divergences such as K-L-divergence,
J-divergence, F-divergence, χ²-divergence, etc.
|
| elki.distance.set |
Distance functions for binary and set type data.
|
| elki.distance.strings |
Distance functions for strings.
|
| elki.distance.subspace |
Distance functions based on subspaces.
|
| elki.distance.timeseries |
Distance functions designed for time series.
|
| elki.evaluation |
Functionality for the evaluation of algorithms.
|
| elki.evaluation.classification |
Evaluation of classification algorithms.
|
| elki.evaluation.classification.holdout |
Holdout and cross-validation strategies for evaluating classifiers.
|
| elki.evaluation.clustering |
Evaluation of clustering results.
|
| elki.evaluation.clustering.extractor |
Classes to extract clusterings from hierarchical clustering.
|
| elki.evaluation.clustering.internal |
Internal evaluation measures for clusterings.
|
| elki.evaluation.clustering.pairsegments |
Pair-segment analysis of multiple clusterings.
|
| elki.evaluation.index |
Simple index evaluation methods.
|
| elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
|
| elki.evaluation.scores |
Evaluation of rankings and scorings.
|
| elki.evaluation.scores.adapter |
Adapter classes for ranking and scoring measures.
|
| elki.evaluation.similaritymatrix |
Render a distance matrix to visualize a clustering-distance-combination.
|
| elki.gui |
Graphical User Interfaces for ELKI.
|
| elki.gui.configurator |
Configurator components.
|
| elki.gui.icons |
Icons for ELKI GUI.
|
| elki.gui.minigui |
A very simple UI to build ELKI command lines.
|
| elki.gui.multistep |
Multi-step GUI for ELKI.
|
| elki.gui.multistep.panels |
Panels for the multi-step GUI.
|
| elki.gui.util |
Utility classes for GUIs (e.g., a class to display a logging panel).
|
| elki.index |
Index structure implementations.
|
| elki.index.distancematrix |
Precomputed distance matrix.
|
| elki.index.idistance |
iDistance is a distance based indexing technique, using a reference points embedding.
|
| elki.index.invertedlist |
Indexes using inverted lists.
|
| elki.index.laesa |
Linear Approximating and Eliminating Search Algorithm (LAESA).
|
| elki.index.lsh |
Locality Sensitive Hashing.
|
| elki.index.lsh.hashfamilies |
Hash function families for LSH.
|
| elki.index.lsh.hashfunctions |
Hash functions for LSH.
|
| elki.index.preprocessed.fastoptics |
Preprocessed index used by the FastOPTICS algorithm.
|
| elki.index.preprocessed.knn |
Indexes providing KNN and rKNN data.
|
| elki.index.preprocessed.snn |
Indexes providing nearest neighbor sets.
|
| elki.index.projected |
Projected indexes for data.
|
| elki.index.tree |
Tree-based index structures.
|
| elki.index.tree.betula |
BETULA clustering by aggregating the data into cluster features.
|
| elki.index.tree.betula.distance |
Distance functions for BETULA and BIRCH.
|
| elki.index.tree.betula.features |
Different variants of Betula and BIRCH cluster features.
|
| elki.index.tree.metrical |
Tree-based index structures for metrical vector spaces.
|
| elki.index.tree.metrical.covertree |
Cover-tree variations.
|
| elki.index.tree.metrical.mtreevariants |
M-tree and variants.
|
| elki.index.tree.metrical.mtreevariants.mktrees |
Metrical index structures based on the concepts of the M-Tree
supporting processing of reverse k nearest neighbor queries by
using the k-nn distances of the entries.
|
| elki.index.tree.metrical.mtreevariants.mktrees.mkapp |
|
| elki.index.tree.metrical.mtreevariants.mktrees.mkcop |
|
| elki.index.tree.metrical.mtreevariants.mktrees.mkmax |
|
| elki.index.tree.metrical.mtreevariants.mktrees.mktab |
|
| elki.index.tree.metrical.mtreevariants.mtree |
|
| elki.index.tree.metrical.mtreevariants.query |
Classes for performing queries (knn, range, ...) on metrical trees.
|
| elki.index.tree.metrical.mtreevariants.strategies.insert |
Insertion (choose path) strategies of nodes in an M-tree (and variants).
|
| elki.index.tree.metrical.mtreevariants.strategies.split |
Splitting strategies of nodes in an M-tree (and variants).
|
| elki.index.tree.metrical.mtreevariants.strategies.split.distribution |
Entry distribution strategies of nodes in an M-tree (and variants).
|
| elki.index.tree.metrical.vptree |
|
| elki.index.tree.spatial |
Tree-based index structures for spatial indexing.
|
| elki.index.tree.spatial.kd |
K-d-tree and variants.
|
| elki.index.tree.spatial.kd.split |
|
| elki.index.tree.spatial.rstarvariants |
R*-tree and variants.
|
| elki.index.tree.spatial.rstarvariants.deliclu |
|
| elki.index.tree.spatial.rstarvariants.flat |
|
| elki.index.tree.spatial.rstarvariants.query |
Queries on the R-Tree family of indexes: kNN and range queries.
|
| elki.index.tree.spatial.rstarvariants.rdknn |
|
| elki.index.tree.spatial.rstarvariants.rstar |
|
| elki.index.tree.spatial.rstarvariants.strategies.bulk |
Packages for bulk-loading R*-trees.
|
| elki.index.tree.spatial.rstarvariants.strategies.insert |
Insertion strategies for R-trees.
|
| elki.index.tree.spatial.rstarvariants.strategies.overflow |
Overflow treatment strategies for R-trees.
|
| elki.index.tree.spatial.rstarvariants.strategies.reinsert |
Reinsertion strategies for R-trees.
|
| elki.index.tree.spatial.rstarvariants.strategies.split |
Splitting strategies for R-trees.
|
| elki.index.tree.spatial.rstarvariants.util |
Utilities for R*-tree and variants.
|
| elki.index.vafile |
Vector Approximation File.
|
| elki.itemsetmining |
Algorithms for frequent itemset mining such as APRIORI.
|
| elki.itemsetmining.associationrules |
Association rule mining.
|
| elki.itemsetmining.associationrules.interest |
Association rule interestingness measures.
|
| elki.logging |
Logging facility for controlling logging behavior of the complete framework.
|
| elki.logging.progress |
Progress status objects (for UI).
|
| elki.logging.statistics |
Classes for logging various statistics.
|
| elki.math |
Mathematical operations and utilities used throughout the framework.
|
| elki.math.geodesy |
Functions for computing on the sphere / earth.
|
| elki.math.geometry |
Algorithms from computational geometry.
|
| elki.math.linearalgebra |
The linear algebra package provides classes and computational methods for
operations on matrices and vectors.
|
| elki.math.linearalgebra.fitting |
|
| elki.math.linearalgebra.pca |
Principal Component Analysis (PCA) and eigenvector processing.
|
| elki.math.linearalgebra.pca.filter |
Filter eigenvectors based on their eigenvalues.
|
| elki.math.linearalgebra.pca.weightfunctions |
|
| elki.math.scales |
Scales handling for plotting.
|
| elki.math.spacefillingcurves |
Space filling curves.
|
| elki.math.statistics |
Statistical tests and methods.
|
| elki.math.statistics.dependence |
Statistical measures of dependence, such as correlation.
|
| elki.math.statistics.dependence.mcde |
|
| elki.math.statistics.distribution |
Standard distributions, with random generation functionalities.
|
| elki.math.statistics.distribution.estimator |
Estimators for statistical distributions.
|
| 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.
|
| elki.math.statistics.intrinsicdimensionality |
Methods for estimating the intrinsic dimensionality.
|
| elki.math.statistics.kernelfunctions |
Kernel functions from statistics.
|
| elki.math.statistics.tests |
Statistical tests.
|
| elki.outlier |
Outlier detection algorithms.
|
| elki.outlier.anglebased |
Angle-based outlier detection algorithms.
|
| elki.outlier.clustering |
Clustering based outlier detection.
|
| elki.outlier.density |
Density-based outlier detection algorithms.
|
| elki.outlier.distance |
Distance-based outlier detection algorithms, such as DBOutlier and kNN.
|
| elki.outlier.distance.parallel |
Parallel implementations of distance-based outlier detectors.
|
| elki.outlier.intrinsic |
Outlier detection algorithms based on intrinsic dimensionality.
|
| elki.outlier.lof |
LOF family of outlier detection algorithms.
|
| elki.outlier.lof.parallel |
Parallelized variants of LOF.
|
| elki.outlier.meta |
Meta outlier detection algorithms: external scores, score rescaling.
|
| elki.outlier.spatial |
Spatial outlier detection algorithms.
|
| elki.outlier.spatial.neighborhood |
Spatial outlier neighborhood classes.
|
| elki.outlier.spatial.neighborhood.weighted |
Weighted neighborhood definitions.
|
| elki.outlier.subspace |
Subspace outlier detection methods.
|
| elki.outlier.svm |
Support-Vector-Machines for outlier detection.
|
| elki.outlier.trivial |
Trivial outlier detection algorithms: no outliers, all outliers, label
outliers.
|
| elki.parallel |
Parallel processing core for ELKI.
|
| elki.parallel.processor |
Processor API of ELKI, and some essential shared processors.
|
| elki.parallel.variables |
Variables are instantiated for each thread, and allow passing values from
one processor to another within the same thread.
|
| elki.persistent |
Persistent data management.
|
| elki.projection |
Data projections (see also preprocessing filters for basic projections).
|
| elki.result |
Result types, representation and handling.
|
| elki.result.outlier |
Outlier result classes.
|
| elki.result.textwriter |
Text serialization (CSV, Gnuplot, Console, ...).
|
| elki.result.textwriter.naming |
Naming schemes for clusters (for output when an algorithm does not generate
cluster names).
|
| elki.result.textwriter.writers |
Serialization handlers for individual data types.
|
| elki.similarity |
Similarity functions.
|
| elki.similarity.cluster |
Similarity measures for comparing clusters.
|
| elki.similarity.kernel |
Kernel functions.
|
| elki.svm |
|
| elki.svm.data |
|
| elki.svm.model |
|
| elki.svm.qmatrix |
|
| elki.svm.solver |
|
| elki.timeseries |
Algorithms for change point detection in time series.
|
| elki.utilities |
Utility and helper classes - commonly used data structures, output
formatting, exceptions, ...
|
| elki.utilities.datastructures |
Basic memory structures such as heaps and object hierarchies.
|
| elki.utilities.datastructures.arraylike |
Common API for accessing objects that are "array-like", including lists,
numerical vectors, database vectors and arrays.
|
| elki.utilities.datastructures.arrays |
Utilities for arrays: advanced sorting for primitive arrays.
|
| elki.utilities.datastructures.heap |
Heap structures and variations such as bounded priority heaps.
|
| elki.utilities.datastructures.hierarchy |
Delegate implementation of a hierarchy.
|
| elki.utilities.datastructures.histogram |
Classes for computing histograms.
|
| elki.utilities.datastructures.iterator |
ELKI Iterator API.
|
| elki.utilities.datastructures.range |
Ranges of values.
|
| elki.utilities.datastructures.unionfind |
Union-find data structures.
|
| elki.utilities.documentation |
Documentation utilities: Annotations for Title, Description, Reference.
|
| elki.utilities.ensemble |
Utility classes for simple ensembles.
|
| elki.utilities.exceptions |
Exception classes and common exception messages.
|
| elki.utilities.io |
Utility classes for input/output.
|
| elki.utilities.optionhandling |
Parameter handling and option descriptions.
|
| elki.utilities.optionhandling.constraints |
Constraints allow to restrict possible values for parameters.
|
| elki.utilities.optionhandling.parameterization |
Configuration managers.
|
| elki.utilities.optionhandling.parameters |
Classes for various typed parameters.
|
| elki.utilities.pairs |
Pairs utility classes.
|
| elki.utilities.random |
Random number generation.
|
| elki.utilities.referencepoints |
Package containing strategies to obtain reference points.
|
| elki.utilities.scaling |
Scaling functions: linear, logarithmic, gamma, clipping, ...
|
| elki.utilities.scaling.outlier |
Scaling of outlier scores, that require a statistical analysis of the
occurring values.
|
| elki.utilities.xml |
XML and XHTML utilities.
|
| elki.visualization |
Visualization package of ELKI.
|
| elki.visualization.batikutil |
Commonly used functionality useful for Apache Batik.
|
| elki.visualization.colors |
Color scheme handling for ELKI visualization.
|
| elki.visualization.css |
Managing CSS styles / classes.
|
| elki.visualization.gui |
Package to provide a visualization GUI.
|
| elki.visualization.gui.detail |
Classes for managing a detail view.
|
| elki.visualization.gui.overview |
Classes for managing the overview plot.
|
| elki.visualization.opticsplot |
Code for drawing OPTICS plots.
|
| elki.visualization.parallel3d |
3DPC: 3D parallel coordinate plot visualization for ELKI.
|
| elki.visualization.parallel3d.layout |
Layouting algorithms for 3D parallel coordinate plots.
|
| elki.visualization.parallel3d.util |
Utility classes (primarily rendering utilities).
|
| elki.visualization.projections |
Visualization projections.
|
| elki.visualization.projector |
Projectors are responsible for finding appropriate projections for data
relations.
|
| elki.visualization.savedialog |
Save dialog for SVG plots.
|
| elki.visualization.silhouette |
Code for drawing silhouette plots.
|
| elki.visualization.style |
Style management for ELKI visualizations.
|
| elki.visualization.style.lines |
Generate line styles for plotting in CSS.
|
| elki.visualization.style.marker |
Draw plot markers.
|
| elki.visualization.svg |
Base SVG functionality (generation, markers, thumbnails, export, ...).
|
| elki.visualization.visualizers |
Visualizers for various results.
|
| elki.visualization.visualizers.actions |
Action-only "visualizers" that only produce menu entries.
|
| elki.visualization.visualizers.histogram |
Visualizers based on 1D projected histograms.
|
| elki.visualization.visualizers.optics |
Visualizers that do work on OPTICS plots.
|
| elki.visualization.visualizers.pairsegments |
Visualizers for inspecting cluster differences using pair counting segments.
|
| elki.visualization.visualizers.parallel |
Visualizers based on parallel coordinates.
|
| elki.visualization.visualizers.parallel.cluster |
Visualizers for clustering results based on parallel coordinates.
|
| elki.visualization.visualizers.parallel.index |
Visualizers for index structure based on parallel coordinates.
|
| elki.visualization.visualizers.parallel.selection |
Visualizers for object selection based on parallel projections.
|
| elki.visualization.visualizers.scatterplot |
Visualizers based on scatterplots.
|
| elki.visualization.visualizers.scatterplot.cluster |
Visualizers for clustering results based on 2D projections.
|
| elki.visualization.visualizers.scatterplot.density |
Visualizers for data set density in a scatterplot projection.
|
| elki.visualization.visualizers.scatterplot.index |
Visualizers for index structures based on 2D projections.
|
| elki.visualization.visualizers.scatterplot.outlier |
Visualizers for outlier scores based on 2D projections.
|
| elki.visualization.visualizers.scatterplot.selection |
Visualizers for object selection based on 2D projections.
|
| elki.visualization.visualizers.scatterplot.uncertain |
Visualizers for uncertain data.
|
| elki.visualization.visualizers.silhouette |
Visualizers that do work on Silhouette plots.
|
| elki.visualization.visualizers.thumbs |
Thumbnail "Visualizers" (that take care of refreshing thumbnails).
|
| elki.visualization.visualizers.visunproj |
Visualizers that do not use a particular projection.
|
| elki.workflow |
Work flow packages, e.g., following the usual KDD model.
|
| tutorial.clustering |
Classes from the tutorial on implementing a custom k-means variation.
|
| tutorial.distancefunction |
Classes from the tutorial on implementing distance functions.
|
| tutorial.javaapi |
Examples how to invoke ELKI from Java.
|
| tutorial.outlier |
Tutorials on implementing outlier detection methods in ELKI.
|