Package | Description |
---|---|
de.lmu.ifi.dbs.elki |
ELKI framework "Environment for Developing KDD-Applications Supported by
Index-Structures".
|
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
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de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
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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 |
Hierarchical agglomerative clustering (HAC).
|
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.hierarchical.linkage |
Linkages for hierarchical clustering.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations
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de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization |
Initialization strategies for k-means.
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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.
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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.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.
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de.lmu.ifi.dbs.elki.algorithm.outlier.distance |
Distance-based outlier detection algorithms, such as DBOutlier and kNN.
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de.lmu.ifi.dbs.elki.algorithm.outlier.distance.parallel |
Parallel implementations of distance-based outlier detectors.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic |
Outlier detection algorithms based on intrinsic dimensionality.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.lof |
LOF family of outlier detection algorithms
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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
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de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood |
Spatial outlier neighborhood classes
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de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted |
Weighted Neighborhood definitions
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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.
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de.lmu.ifi.dbs.elki.algorithm.outlier.trivial |
Trivial outlier detection algorithms: no outliers, all outliers, label
outliers.
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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.
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de.lmu.ifi.dbs.elki.application |
Base classes for standalone applications.
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de.lmu.ifi.dbs.elki.application.cache |
Utility applications for the persistence layer such as distance cache
builders.
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de.lmu.ifi.dbs.elki.application.experiments |
Packaged experiments to make them easy to reproduce.
|
de.lmu.ifi.dbs.elki.application.greedyensemble |
Greedy ensembles for outlier detection.
|
de.lmu.ifi.dbs.elki.data.projection |
Data projections
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de.lmu.ifi.dbs.elki.data.projection.random |
Random projection families
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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.datasource |
Data normalization (and reconstitution) of data sets
|
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.
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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.selection |
Filters for selecting and sorting data to process.
|
de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations
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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.adapter |
Distance functions deriving distances from, e.g., similarity measures
|
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram |
Distance functions using correlations
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de.lmu.ifi.dbs.elki.distance.distancefunction.correlation |
Distance functions using correlations
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de.lmu.ifi.dbs.elki.distance.distancefunction.external |
Distance functions using external data sources
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de.lmu.ifi.dbs.elki.distance.distancefunction.geo |
Geographic (earth) distance functions
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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.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
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de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel |
Kernel functions.
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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
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de.lmu.ifi.dbs.elki.evaluation.clustering.extractor |
Classes to extract clusterings from hierarchical clustering.
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de.lmu.ifi.dbs.elki.evaluation.clustering.internal |
Internal evaluation measures for 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 |
Evaluation of rankings and scorings
|
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix |
Render a distance matrix to visualize a clustering-distance-combination.
|
de.lmu.ifi.dbs.elki.gui.configurator |
Configurator components
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de.lmu.ifi.dbs.elki.gui.minigui |
A very simple UI to build ELKI command lines
|
de.lmu.ifi.dbs.elki.gui.multistep |
Multi-step GUI for ELKI
|
de.lmu.ifi.dbs.elki.gui.multistep.panels |
Panels for the multi-step GUI
|
de.lmu.ifi.dbs.elki.gui.util |
Utility classes for GUIs (e.g. a class to display a logging panel)
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de.lmu.ifi.dbs.elki.index |
Index structure implementations
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de.lmu.ifi.dbs.elki.index.distancematrix |
Precomputed distance matrix.
|
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 |
Locality Sensitive Hashing
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de.lmu.ifi.dbs.elki.index.lsh.hashfamilies |
Hash function families 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 |
M-Tree and variants
|
de.lmu.ifi.dbs.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
|
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp | |
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop | |
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 |
R*-Tree and variants
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn | |
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.vafile |
Vector Approximation File
|
de.lmu.ifi.dbs.elki.math.linearalgebra.pca |
Principal Component Analysis (PCA) and Eigenvector processing
|
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.filter |
Filter eigenvectors based on their eigenvalues.
|
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.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.persistent |
Persistent data management
|
de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
de.lmu.ifi.dbs.elki.utilities |
Utility and helper classes - commonly used data structures, output
formatting, exceptions, ...
|
de.lmu.ifi.dbs.elki.utilities.ensemble |
Utility classes for simple ensembles
|
de.lmu.ifi.dbs.elki.utilities.optionhandling |
Parameter handling and option descriptions.
|
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization |
Configuration managers
See the
de.lmu.ifi.dbs.elki.utilities.optionhandling package for
documentation! |
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters |
Classes for various typed parameters
See the
de.lmu.ifi.dbs.elki.utilities.optionhandling package for
documentation! |
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.utilities.scaling |
Scaling functions: linear, logarithmic, gamma, clipping, ...
|
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 |
Visualization package of ELKI
|
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.projector |
Projectors are responsible for finding appropriate projections for data
relations
|
de.lmu.ifi.dbs.elki.visualization.visualizers.histogram |
Visualizers based on 1D projected histograms
|
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster |
Visualizers for clustering results based on parallel coordinates
|
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.index |
Visualizers for index structure based on parallel coordinates
|
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.index |
Visualizers for index structures based on 2D projections
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier |
Visualizers for outlier scores 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
|
de.lmu.ifi.dbs.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.outlier |
Tutorials on implementing outlier detection methods in ELKI.
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Class and Description |
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Parameterization
Interface for object parameterizations.
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TrackedParameter
Class containing an object, and the associated value.
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Class and Description |
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Parameterization
Interface for object parameterizations.
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Parameterization
Interface for object parameterizations.
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Interface for object parameterizations.
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Parameterization
Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Class and Description |
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Interface for object parameterizations.
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Class and Description |
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Parameterization
Interface for object parameterizations.
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TrackedParameter
Class containing an object, and the associated value.
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Class and Description |
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Parameterization
Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Parameterization
Interface for object parameterizations.
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Class and Description |
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ListParameterization
Parameterization handler using a List and OptionIDs, for programmatic use.
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TrackParameters
Utility wrapper to track parameters for a configuration session.
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SerializedParameterization
Manage a parameterization serialized as String array, e.g. from command line.
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Class and Description |
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Parameterization
Interface for object parameterizations.
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Class and Description |
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ListParameterization
Parameterization handler using a List and OptionIDs, for programmatic use.
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Parameterization
Interface for object parameterizations.
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Class and Description |
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TrackParameters
Utility wrapper to track parameters for a configuration session.
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Class and Description |
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Parameterization
Interface for object parameterizations.
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Parameterization
Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Interface for object parameterizations.
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Parameterization
Interface for object parameterizations.
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Interface for object parameterizations.
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Parameterization
Interface for object parameterizations.
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Class and Description |
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Parameterization
Interface for object parameterizations.
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Class and Description |
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Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
TrackedParameter
Class containing an object, and the associated value.
|
Class and Description |
---|
ListParameterization
Parameterization handler using a List and OptionIDs, for programmatic use.
|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
TrackedParameter
Class containing an object, and the associated value.
|
Class and Description |
---|
AbstractParameterization
Abstract class with shared code for parameterization handling.
|
ListParameterization
Parameterization handler using a List and OptionIDs, for programmatic use.
|
ListParameterization.ParameterPair
Parameter pair, package-private.
|
Parameterization
Interface for object parameterizations.
|
TrackedParameter
Class containing an object, and the associated value.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
MergedParameterization
This configuration can be "rewound" to allow the same values to be consumed
multiple times, by different classes.
|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Class and Description |
---|
Parameterization
Interface for object parameterizations.
|
Copyright © 2019 ELKI Development Team. License information.