Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm |
Algorithms suitable as a task for the
KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.benchmark |
Benchmarking pseudo algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.classification |
Classification algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering |
Clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation |
Affinity Propagation (AP) clustering.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering |
Biclustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.algorithm.clustering.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.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.trivial |
Trivial clustering algorithms: all in one, no clusters, label clusterings
These methods are mostly useful for providing a reference result in evaluation.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain |
Clustering algorithms for uncertain data.
|
de.lmu.ifi.dbs.elki.algorithm.itemsetmining |
Algorithms for frequent itemset mining such as APRIORI.
|
de.lmu.ifi.dbs.elki.algorithm.outlier |
Outlier detection algorithms
|
de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased |
Angle-based outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.clustering |
Clustering based outlier detection.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.distance |
Distance-based outlier detection algorithms, such as DBOutlier and kNN.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.lof |
LOF family of outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.meta |
Meta outlier detection algorithms: external scores, score rescaling.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial |
Spatial outlier detection algorithms
|
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood |
Spatial outlier neighborhood classes
|
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted |
Weighted Neighborhood definitions.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.svm |
Support-Vector-Machines for outlier detection.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.trivial |
Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms
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.cache |
Utility applications for the persistence layer such as distance cache builders.
|
de.lmu.ifi.dbs.elki.application.experiments |
Packaged experiments to make them easy to reproduce.
|
de.lmu.ifi.dbs.elki.application.geo |
Application for exploring geo data.
|
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.application.jsmap |
JavaScript based map client - server architecture.
|
de.lmu.ifi.dbs.elki.data.projection |
Data projections.
|
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.
|
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.
|
de.lmu.ifi.dbs.elki.datasource.filter.typeconversions |
Filters to perform data type conversions.
|
de.lmu.ifi.dbs.elki.datasource.parser |
Parsers for different file formats and data types.
|
de.lmu.ifi.dbs.elki.distance.distancefunction |
Distance functions for use within ELKI.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.adapter |
Distance functions deriving distances from e.g. similarity measures
|
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.minkowski |
Minkowski space L_p 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.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction |
Similarity functions.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel |
Kernel functions.
|
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.histogram |
Functionality for the evaluation of algorithms using histograms.
|
de.lmu.ifi.dbs.elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
|
de.lmu.ifi.dbs.elki.evaluation.scores |
Evaluation of rankings and scorings.
|
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix |
Render a distance matrix to visualize a clustering-distance-combination.
|
de.lmu.ifi.dbs.elki.gui.util |
Utility classes for GUIs (e.g. a class to display a logging panel)
|
de.lmu.ifi.dbs.elki.index |
Index structure implementations
|
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
|
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.geodesy | |
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.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.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.
|
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.gui |
Package to provide a visualization GUI.
|
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.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.workflow |
Work flow packages, e.g. following the usual KDD model, closely related to CRISP-DM
|
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 |
Modifier and Type | Field and Description |
---|---|
static OptionID |
DependencyDerivator.DEPENDENCY_DERIVATOR_RANDOM_SAMPLE
Flag to use random sample (use knn query around centroid, if flag is not
set).
|
static OptionID |
DistanceBasedAlgorithm.DISTANCE_FUNCTION_ID
OptionID for
DistanceBasedAlgorithm.DISTANCE_FUNCTION_ID . |
static OptionID |
KNNJoin.Parameterizer.K_ID
Parameter that specifies the k-nearest neighbors to be assigned, must be an
integer greater than 0.
|
static OptionID |
KNNDistancesSampler.Parameterizer.K_ID
Parameter to specify the distance of the k-distant object to be assessed,
must be an integer greater than 0.
|
static OptionID |
DependencyDerivator.OUTPUT_ACCURACY_ID
Parameter to specify the threshold for output accuracy fraction digits,
must be an integer equal to or greater than 0.
|
static OptionID |
DependencyDerivator.SAMPLE_SIZE_ID
Optional parameter to specify the threshold for the size of the random
sample to use, must be an integer greater than 0.
|
static OptionID |
KNNDistancesSampler.Parameterizer.SAMPLING_ID
Parameter to specify the average percentage of distances randomly chosen
to be provided in the result, must be a double greater than 0 and less
than or equal to 1.
|
static OptionID |
KNNDistancesSampler.Parameterizer.SEED_ID
Random generator seed for distances.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.FORCE_ID
Force linear scanning.
|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.K_ID
Parameter for the number of neighbors.
|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.K_ID
Parameter for the number of neighbors.
|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.PATTERN_ID
Parameter to select query points.
|
static OptionID |
RangeQueryBenchmarkAlgorithm.Parameterizer.QUERY_ID
Parameter for the query dataset.
|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.QUERY_ID
Parameter for the query dataset.
|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.QUERY_ID
Parameter for the query dataset.
|
static OptionID |
RangeQueryBenchmarkAlgorithm.Parameterizer.RANDOM_ID
Parameter for the random generator
|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.RANDOM_ID
Parameter for the random generator
|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.RANDOM_ID
Parameter for the random generator.
|
static OptionID |
RangeQueryBenchmarkAlgorithm.Parameterizer.SAMPLING_ID
Parameter for the sampling size.
|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.SAMPLING_ID
Parameter for the sampling size.
|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.SAMPLING_ID
Parameter for the sampling size.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
KNNClassifier.Parameterizer.K_ID
Parameter to specify the number of neighbors to take into account for
classification, must be an integer greater than 0.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
SNNClustering.Parameterizer.EPSILON_ID
Parameter to specify the minimum SNN density, must be an integer greater
than 0.
|
static OptionID |
DBSCAN.Parameterizer.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to the distance function specified.
|
static OptionID |
AbstractProjectedClustering.Parameterizer.K_I_ID
Parameter to specify the multiplier for the initial number of seeds, must
be an integer greater than 0.
|
static OptionID |
AbstractProjectedClustering.Parameterizer.K_ID
Parameter to specify the number of clusters to find, must be an integer
greater than 0.
|
static OptionID |
NaiveMeanShiftClustering.Parameterizer.KERNEL_ID
Parameter for kernel function.
|
static OptionID |
AbstractProjectedClustering.Parameterizer.L_ID
Parameter to specify the dimensionality of the clusters to find, must be
an integer greater than 0.
|
static OptionID |
SNNClustering.Parameterizer.MINPTS_ID
Parameter to specify the threshold for minimum number of points in the
epsilon-SNN-neighborhood of a point, must be an integer greater than 0.
|
static OptionID |
DBSCAN.Parameterizer.MINPTS_ID
Parameter to specify the threshold for minimum number of points in the
epsilon-neighborhood of a point, must be an integer greater than 0.
|
static OptionID |
NaiveMeanShiftClustering.Parameterizer.RANGE_ID
Parameter for kernel radius/range/bandwidth.
|
static OptionID |
CanopyPreClustering.Parameterizer.T1_ID
Parameter for the inclusion threshold of canopy clustering.
|
static OptionID |
CanopyPreClustering.Parameterizer.T2_ID
Parameter for the removal threshold of canopy clustering.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AffinityPropagationClusteringAlgorithm.Parameterizer.CONVERGENCE_ID
Parameter for the convergence factor.
|
static OptionID |
DistanceBasedInitializationWithMedian.Parameterizer.DISTANCE_ID
Parameter for the distance function.
|
static OptionID |
AffinityPropagationClusteringAlgorithm.Parameterizer.INITIALIZATION_ID
Parameter for the similarity matrix initialization
|
static OptionID |
AffinityPropagationClusteringAlgorithm.Parameterizer.LAMBDA_ID
Parameter for the dampening factor.
|
static OptionID |
AffinityPropagationClusteringAlgorithm.Parameterizer.MAXITER_ID
Parameter for the convergence factor.
|
static OptionID |
AffinityPropagationInitialization.QUANTILE_ID
Quantile to use for the diagonal entries.
|
static OptionID |
SimilarityBasedInitializationWithMedian.Parameterizer.SIMILARITY_ID
Parameter for the similarity function.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ChengAndChurch.Parameterizer.ALPHA_ID
Parameter for multiple node deletion to accelerate the algorithm.
|
static OptionID |
ChengAndChurch.Parameterizer.DELTA_ID
Threshold value to determine the maximal acceptable score (mean squared
residue) of a bicluster.
|
static OptionID |
ChengAndChurch.Parameterizer.DIST_ID
Parameter to specify the distribution of replacement values when masking
a cluster.
|
static OptionID |
ChengAndChurch.Parameterizer.N_ID
Number of biclusters to be found.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CASH.ADJUST_ID
Flag to indicate that an adjustment of the applied heuristic for choosing
an interval is performed after an interval is selected.
|
static OptionID |
ORCLUS.Parameterizer.ALPHA_ID
Parameter to specify the factor for reducing the number of current
clusters in each iteration, must be an integer greater than 0 and less
than 1.
|
static OptionID |
HiCO.Parameterizer.ALPHA_ID
The threshold for 'strong' eigenvectors: the 'strong' eigenvectors
explain a portion of at least alpha of the total variance.
|
static OptionID |
ERiC.Settings.Parameterizer.DELTA_ID
Parameter to specify the threshold for approximate linear dependency:
the strong eigenvectors of q are approximately linear dependent from
the strong eigenvectors p if the following condition holds for all
strong eigenvectors q_i of q (lambda_q < lambda_p): q_i' * M^check_p *
q_i <= delta^2, must be a double equal to or greater than 0.
|
static OptionID |
HiCO.Parameterizer.DELTA_ID
Parameter to specify the threshold of a distance between a vector q and a
given space that indicates that q adds a new dimension to the space, must
be a double equal to or greater than 0.
|
static OptionID |
CASH.JITTER_ID
Parameter to specify the maximum jitter for distance values, must be a
double greater than 0.
|
static OptionID |
COPAC.Settings.Parameterizer.K_ID
Size for the kNN neighborhood used in the PCA step of COPAC.
|
static OptionID |
ERiC.Settings.Parameterizer.K_ID
Size for the kNN neighborhood used in the PCA step of ERiC.
|
static OptionID |
HiCO.Parameterizer.K_ID
Optional parameter to specify the number of nearest neighbors considered
in the PCA, must be an integer greater than 0.
|
static OptionID |
FourC.Settings.Parameterizer.KAPPA_ID
Parameter Kappa: penalty for deviations in preferred dimensions.
|
static OptionID |
FourC.Settings.Parameterizer.LAMBDA_ID
Parameter Lambda: maximum dimensionality allowed.
|
static OptionID |
LMCLUS.Parameterizer.MAXDIM_ID
Parameter with the maximum dimension to search for
|
static OptionID |
CASH.MAXLEVEL_ID
Parameter to specify the maximum level for splitting the hypercube, must be
an integer greater than 0.
|
static OptionID |
CASH.MINDIM_ID
Parameter to specify the minimum dimensionality of the subspaces to be
found, must be an integer greater than 0.
|
static OptionID |
CASH.MINPTS_ID
Parameter to specify the threshold for minimum number of points in a
cluster, must be an integer greater than 0.
|
static OptionID |
LMCLUS.Parameterizer.MINSIZE_ID
Parameter for the minimum cluster size
|
static OptionID |
HiCO.Parameterizer.MU_ID
Parameter to specify the smoothing factor, must be an integer greater
than 0.
|
static OptionID |
LMCLUS.Parameterizer.RANDOM_ID
Random seeding
|
static OptionID |
LMCLUS.Parameterizer.SAMPLINGL_ID
Sampling intensity level
|
static OptionID |
ORCLUS.Parameterizer.SEED_ID
Parameter to specify the random generator seed.
|
static OptionID |
ERiC.Settings.Parameterizer.TAU_ID
Parameter to specify the threshold for the maximum distance between two
approximately linear dependent subspaces of two objects p and q
(lambda_q < lambda_p) before considering them as parallel, must be a
double equal to or greater than 0.
|
static OptionID |
LMCLUS.Parameterizer.THRESHOLD_ID
Global significance threshold
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
EM.Parameterizer.DELTA_ID
Parameter to specify the termination criterion for maximization of E(M):
E(M) - E(M') < em.delta, must be a double equal to or greater than 0.
|
static OptionID |
AbstractEMModelFactory.Parameterizer.INIT_ID
Parameter to specify the cluster center initialization.
|
static OptionID |
EM.Parameterizer.INIT_ID
Parameter to specify the EM cluster models to use.
|
static OptionID |
EM.Parameterizer.K_ID
Parameter to specify the number of clusters to find, must be an integer
greater than 0.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
LSDBC.Parameterizer.ALPHA_ID
Parameter for the maximum density difference.
|
static OptionID |
GeneralizedDBSCAN.Parameterizer.COREMODEL_ID
Flag to keep track of core points.
|
static OptionID |
GeneralizedDBSCAN.Parameterizer.COREPRED_ID
Parameter for core predicate.
|
static OptionID |
LSDBC.Parameterizer.K_ID
Parameter for neighborhood size.
|
static OptionID |
GeneralizedDBSCAN.Parameterizer.NEIGHBORHOODPRED_ID
Parameter for neighborhood predicate.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AGNES.Parameterizer.LINKAGE_ID
Option ID for linkage parameter.
|
static OptionID |
AbstractHDBSCAN.Parameterizer.MIN_PTS_ID
Option ID for linkage parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
HDBSCANHierarchyExtraction.Parameterizer.HIERARCHICAL_ID
Produce a hierarchical result.
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.MINCLUSTERS_ID
The minimum number of clusters to extract.
|
static OptionID |
HDBSCANHierarchyExtraction.Parameterizer.MINCLUSTERSIZE_ID
The minimum size of clusters to extract.
|
static OptionID |
SimplifiedHierarchyExtraction.Parameterizer.MINCLUSTERSIZE_ID
The minimum size of clusters to extract.
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.MODE_ID
Extraction mode to use.
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.OUTPUTMODE_ID
Parameter to configure the output mode (nested or truncated clusters).
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.SINGLETONS_ID
Flag to produce singleton clusters.
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.THRESHOLD_ID
The threshold level for which to extract the clustering.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
KMeansBatchedLloyd.Parameterizer.BLOCKS_ID
Parameter for the number of blocks.
|
static OptionID |
XMeans.Parameterizer.INFORMATION_CRITERION_ID
Quality measure to use for evaluating splits.
|
static OptionID |
KMeans.INIT_ID
Parameter to specify the initialization method
|
static OptionID |
XMeans.Parameterizer.INNER_KMEANS_ID
Parameter to specify the kMeans variant.
|
static OptionID |
KMeans.K_ID
Parameter to specify the number of clusters to find, must be an integer
greater than 0.
|
static OptionID |
XMeans.Parameterizer.K_MIN_ID
Minimum number of clusters.
|
static OptionID |
KMeansBisecting.Parameterizer.KMEANS_ID
Parameter to specify the kMeans variant.
|
static OptionID |
BestOfMultipleKMeans.Parameterizer.KMEANS_ID
Parameter to specify the kMeans variant.
|
static OptionID |
KMeans.MAXITER_ID
Parameter to specify the number of clusters to find, must be an integer
greater or equal to 0, where 0 means no limit.
|
static OptionID |
CLARA.Parameterizer.NUMSAMPLES_ID
The number of samples to run.
|
static OptionID |
BestOfMultipleKMeans.Parameterizer.QUALITYMEASURE_ID
Parameter to specify the variant of quality measure.
|
static OptionID |
KMeansBatchedLloyd.Parameterizer.RANDOM_ID
Random source for blocking.
|
static OptionID |
CLARA.Parameterizer.RANDOM_ID
Random generator.
|
static OptionID |
CLARA.Parameterizer.SAMPLESIZE_ID
The sample size.
|
static OptionID |
KMeans.SEED_ID
Parameter to specify the random generator seed.
|
static OptionID |
XMeans.Parameterizer.SEED_ID
Randomization seed.
|
static OptionID |
BestOfMultipleKMeans.Parameterizer.TRIALS_ID
Parameter to specify the iterations of the bisecting step.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PredefinedInitialMeans.Parameterizer.INITIAL_MEANS
Option to specify the initial means to use.
|
static OptionID |
FarthestPointsInitialMeans.Parameterizer.KEEPFIRST_ID
Option ID to control the handling of the first object chosen.
|
static OptionID |
SampleKMeansInitialization.Parameterizer.KMEANS_ID
Parameter to specify the kMeans variant.
|
static OptionID |
SampleKMeansInitialization.Parameterizer.SAMPLE_ID
Parameter to specify the sampling rate.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ExternalClustering.Parameterizer.FILE_ID
Parameter that specifies the name of the file to be re-parsed.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
KNNKernelDensityMinimaClustering.Parameterizer.DIM_ID
Dimension to use for clustering.
|
static OptionID |
KNNKernelDensityMinimaClustering.Parameterizer.K_ID
Number of neighbors for bandwidth estimation.
|
static OptionID |
KNNKernelDensityMinimaClustering.Parameterizer.KERNEL_ID
Kernel function.
|
static OptionID |
KNNKernelDensityMinimaClustering.Parameterizer.MODE_ID
KDE mode.
|
static OptionID |
KNNKernelDensityMinimaClustering.Parameterizer.WINDOW_ID
Half window width to find local minima.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractOPTICS.Parameterizer.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to the distance function specified.
|
static OptionID |
OPTICSXi.Parameterizer.KEEPSTEEP_ID
Parameter to keep the steep areas
|
static OptionID |
DeLiClu.Parameterizer.MINPTS_ID
Parameter to specify the threshold for minimum number of points within a
cluster, must be an integer greater than 0.
|
static OptionID |
AbstractOPTICS.Parameterizer.MINPTS_ID
Parameter to specify the threshold for minimum number of points in the
epsilon-neighborhood of a point, must be an integer greater than 0.
|
static OptionID |
OPTICSXi.Parameterizer.NOCORRECT_ID
Parameter to disable the correction function.
|
static OptionID |
OPTICSXi.Parameterizer.XI_ID
Parameter to specify the steepness threshold.
|
static OptionID |
OPTICSXi.Parameterizer.XIALG_ID
Parameter to specify the actual OPTICS algorithm to use.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
DOC.Parameterizer.ALPHA_ID
Relative density threshold parameter Alpha.
|
static OptionID |
P3C.Parameterizer.ALPHA_THRESHOLD_ID
Parameter for the chi squared test threshold.
|
static OptionID |
DOC.Parameterizer.BETA_ID
Balancing parameter for importance of points vs. dimensions
|
static OptionID |
DOC.Parameterizer.D_ZERO_ID
Stopping threshold for FastDOC.
|
static OptionID |
PreDeCon.Settings.Parameterizer.DELTA_ID
Parameter Delta: maximum variance allowed
|
static OptionID |
SUBCLU.DISTANCE_FUNCTION_ID
The distance function to determine the distance between database objects.
|
static OptionID |
P3C.Parameterizer.EM_DELTA_ID
Threshold when to stop EM iterations.
|
static OptionID |
DiSH.Parameterizer.EPSILON_ID
Parameter that specifies the maximum radius of the neighborhood to be
considered in each dimension for determination of the preference vector,
must be a double equal to or greater than 0.
|
static OptionID |
SUBCLU.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to
DimensionSelectingSubspaceDistanceFunction . |
static OptionID |
HiSC.Parameterizer.EPSILON_ID
Parameter to specify the maximum distance between two vectors with equal
preference vectors before considering them as parallel, must be a double
equal to or greater than 0.
|
static OptionID |
DOC.Parameterizer.HEURISTICS_ID
Parameter to enable FastDOC heuristics.
|
static OptionID |
PreDeCon.Settings.Parameterizer.KAPPA_ID
Parameter Kappa: penalty for deviations in preferred dimensions.
|
static OptionID |
PreDeCon.Settings.Parameterizer.LAMBDA_ID
Parameter Lambda: maximum dimensionality allowed.
|
static OptionID |
PROCLUS.Parameterizer.M_I_ID
Parameter to specify the multiplier for the initial number of medoids,
must be an integer greater than 0.
|
static OptionID |
P3C.Parameterizer.MAX_EM_ITERATIONS_ID
Maximum number of iterations for the EM step.
|
static OptionID |
P3C.Parameterizer.MIN_CLUSTER_SIZE_ID
Minimum cluster size for noise flagging.
|
static OptionID |
SUBCLU.MINPTS_ID
Parameter to specify the threshold for minimum number of points in the
epsilon-neighborhood of a point, must be an integer greater than 0.
|
static OptionID |
DiSH.Parameterizer.MU_ID
Parameter that specifies the a minimum number of points as a smoothing
factor to avoid the single-link-effect, must be an integer greater than
0.
|
static OptionID |
P3C.Parameterizer.POISSON_THRESHOLD_ID
Parameter for the poisson test threshold.
|
static OptionID |
CLIQUE.PRUNE_ID
Flag to indicate that only subspaces with large coverage (i.e. the fraction
of the database that is covered by the dense units) are selected, the rest
will be pruned.
|
static OptionID |
DOC.Parameterizer.RANDOM_ID
Random seeding parameter.
|
static OptionID |
PROCLUS.Parameterizer.SEED_ID
Parameter to specify the random generator seed.
|
static OptionID |
CLIQUE.TAU_ID
Parameter to specify the density threshold for the selectivity of a unit,
where the selectivity is the fraction of total feature vectors contained in
this unit, must be a double greater than 0 and less than 1.
|
static OptionID |
DOC.Parameterizer.W_ID
Half width parameter.
|
static OptionID |
CLIQUE.XSI_ID
Parameter to specify the number of intervals (units) in each dimension,
must be an integer greater than 0.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ByLabelClustering.MULTIPLE_ID
Flag to indicate that multiple cluster assignment is possible.
|
static OptionID |
ByLabelClustering.NOISE_ID
Pattern to recognize noise clusters by.
|
static OptionID |
ByModelClustering.NOISE_ID
Pattern to recognize noise clusters with
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
RepresentativeUncertainClustering.Parameterizer.ALGORITHM_ID
Parameter to hand an algorithm to be wrapped and run to our instance of
RepresentativeUncertainClustering . |
static OptionID |
RepresentativeUncertainClustering.Parameterizer.ALPHA_ID
Alpha parameter for confidence estimation.
|
static OptionID |
RepresentativeUncertainClustering.Parameterizer.CLUSTERDISTANCE_ID
Distance function to measure the similarity of clusterings.
|
static OptionID |
RepresentativeUncertainClustering.Parameterizer.KEEP_SAMPLES_ID
Flag to keep all samples.
|
static OptionID |
RepresentativeUncertainClustering.Parameterizer.META_ALGORITHM_ID
Parameter to hand an algorithm for creating the meta-clustering to our
instance of
RepresentativeUncertainClustering . |
static OptionID |
RepresentativeUncertainClustering.Parameterizer.RANDOM_ID
Parameter to specify the random generator.
|
static OptionID |
FDBSCANNeighborPredicate.Parameterizer.SAMPLE_SIZE_ID
Number of samples per uncertain object.
|
static OptionID |
RepresentativeUncertainClustering.Parameterizer.SAMPLES_ID
Parameter to specify the amount of clusterings that shall be created and
compared.
|
static OptionID |
FDBSCANNeighborPredicate.Parameterizer.SEED_ID
Seed for random sample draw.
|
static OptionID |
FDBSCANNeighborPredicate.Parameterizer.THRESHOLD_ID
Threshold for epsilon-neighborhood, defaults to 0.5.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractFrequentItemsetAlgorithm.Parameterizer.MAXLENGTH_ID
Parameter to specify the maximum itemset length.
|
static OptionID |
AbstractFrequentItemsetAlgorithm.Parameterizer.MINLENGTH_ID
Parameter to specify the minimum itemset length.
|
static OptionID |
AbstractFrequentItemsetAlgorithm.Parameterizer.MINSUPP_ID
Parameter to specify the minimum support, in absolute or relative terms.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
GaussianUniformMixture.Parameterizer.C_ID
Parameter to specify the cutoff.
|
static OptionID |
DWOF.Parameterizer.DELTA_ID
Option ID for radius increases
|
static OptionID |
COP.Parameterizer.DIST_ID
Distribution assumption for distances.
|
static OptionID |
COP.Parameterizer.EXPECT_ID
Expected share of outliers.
|
static OptionID |
GaussianModel.INVERT_ID
OptionID for inversion flag.
|
static OptionID |
COP.Parameterizer.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its COP_SCORE, must be an integer greater than
0.
|
static OptionID |
DWOF.Parameterizer.K_ID
Option ID for the number of neighbors.
|
static OptionID |
SimpleCOP.Parameterizer.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its COP_SCORE, must be an integer greater than
0.
|
static OptionID |
GaussianUniformMixture.Parameterizer.L_ID
Parameter to specify the fraction of expected outliers.
|
static OptionID |
COP.Parameterizer.MODELS_ID
Include COP error vectors in output.
|
static OptionID |
COP.Parameterizer.PCARUNNER_ID
Class to compute the PCA with.
|
static OptionID |
SimpleCOP.Parameterizer.PCARUNNER_ID
Parameter for the PCA runner class.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
FastABOD.Parameterizer.K_ID
Parameter for the nearest neighbors.
|
static OptionID |
ABOD.Parameterizer.KERNEL_FUNCTION_ID
Parameter for the kernel function.
|
static OptionID |
LBABOD.Parameterizer.L_ID
Parameter to specify the number of outliers to compute exactly.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
SilhouetteOutlierDetection.Parameterizer.CLUSTERING_ID
Parameter for choosing the clustering algorithm
|
static OptionID |
KMeansOutlierDetection.Parameterizer.CLUSTERING_ID
Parameter for choosing the clustering algorithm.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractDBOutlier.Parameterizer.D_ID
Parameter to specify the size of the D-neighborhood
|
static OptionID |
HilOut.Parameterizer.H_ID
Parameter to specify the maximum Hilbert-Level
|
static OptionID |
ODIN.Parameterizer.K_ID
Parameter for the number of nearest neighbors:
-odin.k <int>
|
static OptionID |
ReferenceBasedOutlierDetection.Parameterizer.K_ID
Parameter to specify the number of nearest neighbors of an object, to be
considered for computing its REFOD_SCORE, must be an integer greater than
1.
|
static OptionID |
KNNOutlier.Parameterizer.K_ID
Parameter to specify the k nearest neighbor
|
static OptionID |
HilOut.Parameterizer.K_ID
Parameter to specify how many next neighbors should be used in the
computation
|
static OptionID |
KNNWeightOutlier.Parameterizer.K_ID
Parameter to specify the k nearest neighbor.
|
static OptionID |
HilOut.Parameterizer.N_ID
Parameter to specify how many outliers should be computed
|
static OptionID |
DBOutlierDetection.Parameterizer.P_ID
Parameter to specify the minimum fraction of objects that must be outside
the D- neighborhood of an outlier
|
static OptionID |
ReferenceBasedOutlierDetection.Parameterizer.REFP_ID
Parameter for the reference points heuristic.
|
static OptionID |
HilOut.Parameterizer.T_ID
Parameter to specify p of LP-NormDistance
|
static OptionID |
HilOut.Parameterizer.TN_ID
Parameter to specify if only the Top n, or also approximations for the
other elements, should be returned
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
LOCI.ALPHA_ID
Parameter to specify the averaging neighborhood scaling.
|
static OptionID |
ALOCI.Parameterizer.ALPHA_ID
Parameter to specify the averaging neighborhood scaling.
|
static OptionID |
LDF.Parameterizer.C_ID
Option ID for c
|
static OptionID |
LoOP.Parameterizer.COMPARISON_DISTANCE_FUNCTION_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
ALOCI.Parameterizer.GRIDS_ID
Parameter to specify the number of Grids to use.
|
static OptionID |
LDF.Parameterizer.H_ID
Option ID for h - kernel bandwidth scaling
|
private static OptionID |
KDEOS.Parameterizer.IDIM_ID
Intrinsic dimensionality.
|
static OptionID |
LDF.Parameterizer.K_ID
Option ID for k
|
static OptionID |
INFLO.Parameterizer.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its INFLO score.
|
static OptionID |
COF.Parameterizer.K_ID
Parameter to specify the neighborhood size for COF.
|
static OptionID |
LOF.Parameterizer.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its LOF score, must be an integer greater than
or equal to 1.
|
static OptionID |
LDOF.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its LDOF_SCORE, must be an integer greater than 1.
|
static OptionID |
LoOP.Parameterizer.KCOMP_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its LOOP_SCORE, must be an integer greater than
1.
|
static OptionID |
LDF.Parameterizer.KERNEL_ID
Option ID for kernel.
|
private static OptionID |
KDEOS.Parameterizer.KERNEL_ID
Parameter to specify the kernel density function.
|
static OptionID |
SimpleKernelDensityLOF.Parameterizer.KERNEL_ID
Option ID for kernel density LOF kernel.
|
private static OptionID |
KDEOS.Parameterizer.KERNEL_MIN_ID
Parameter to specify the minimum bandwidth.
|
private static OptionID |
KDEOS.Parameterizer.KERNEL_SCALE_ID
Parameter to specify the kernel scaling factor.
|
private static OptionID |
KDEOS.Parameterizer.KMAX_ID
Maximum value of k to analyze.
|
private static OptionID |
KDEOS.Parameterizer.KMIN_ID
Minimum value of k to analyze.
|
static OptionID |
FlexibleLOF.Parameterizer.KREACH_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its reachability distance.
|
static OptionID |
LoOP.Parameterizer.KREACH_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its LOOP_SCORE, must be an integer greater than
1.
|
static OptionID |
FlexibleLOF.Parameterizer.KREF_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its LOF score, must be an integer greater or
equal to 1.
|
static OptionID |
LoOP.Parameterizer.LAMBDA_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its LOOP_SCORE, must be an integer greater than
1.
|
static OptionID |
INFLO.Parameterizer.M_ID
Parameter to specify if any object is a Core Object must be a double
greater than 0.0
see paper "Two-way search method" 3.2
|
static OptionID |
LOCI.NMIN_ID
Parameter to specify the minimum neighborhood size
|
static OptionID |
ALOCI.Parameterizer.NMIN_ID
Parameter to specify the minimum neighborhood size
|
static OptionID |
FlexibleLOF.Parameterizer.REACHABILITY_DISTANCE_FUNCTION_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
LoOP.Parameterizer.REACHABILITY_DISTANCE_FUNCTION_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
LOCI.RMAX_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to the distance function specified.
|
static OptionID |
ALOCI.Parameterizer.SEED_ID
Parameter to specify the seed to initialize Random.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
HiCS.Parameterizer.ALGO_ID
Parameter that specifies which outlier detection algorithm to use on the
resulting set of high contrast subspaces.
|
static OptionID |
HiCS.Parameterizer.ALPHA_ID
Parameter that determines the size of the test statistic during the
Monte-Carlo iteration.
|
static OptionID |
FeatureBagging.Parameterizer.BREADTH_ID
The flag for using the breadth first approach.
|
static OptionID |
ExternalDoubleOutlierScore.Parameterizer.FILE_ID
Parameter that specifies the name of the file to be re-parsed.
|
static OptionID |
ExternalDoubleOutlierScore.Parameterizer.ID_ID
Parameter that specifies the object ID pattern
Key:
-externaloutlier.idpattern Default: ^ID= |
static OptionID |
ExternalDoubleOutlierScore.Parameterizer.INVERTED_ID
Flag parameter for inverted scores.
|
static OptionID |
HiCS.Parameterizer.LIMIT_ID
Parameter that specifies the candidate_cutoff.
|
static OptionID |
HiCS.Parameterizer.M_ID
Parameter that specifies the number of iterations in the Monte-Carlo
process of identifying high contrast subspaces.
|
static OptionID |
FeatureBagging.Parameterizer.NUM_ID
Parameter to specify the number of instances to use in the ensemble.
|
static OptionID |
ExternalDoubleOutlierScore.Parameterizer.SCALING_ID
Parameter to specify a scaling function to use.
|
static OptionID |
RescaleMetaOutlierAlgorithm.SCALING_ID
Parameter to specify a scaling function to use.
|
static OptionID |
ExternalDoubleOutlierScore.Parameterizer.SCORE_ID
Parameter that specifies the object score pattern
Key:
-externaloutlier.scorepattern |
static OptionID |
HiCS.Parameterizer.SEED_ID
Parameter that specifies the random seed.
|
static OptionID |
FeatureBagging.Parameterizer.SEED_ID
The parameter to specify the random seed.
|
static OptionID |
HiCS.Parameterizer.TEST_ID
Parameter that specifies which statistical test to use in order to
calculate the deviation of two given data samples.
|
static OptionID |
SimpleOutlierEnsemble.Parameterizer.VOTING_ID
Voting strategy to use in the ensemble.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CTLuGLSBackwardSearchAlgorithm.Parameterizer.ALPHA_ID
Holds the alpha value - significance niveau
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.ALPHA_ID
Parameter to specify alpha.
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.C_ID
Parameter to specify the c.
|
static OptionID |
CTLuGLSBackwardSearchAlgorithm.Parameterizer.K_ID
Parameter to specify the k nearest neighbors
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.K_ID
Parameter to specify the number of neighbors.
|
static OptionID |
AbstractNeighborhoodOutlier.NEIGHBORHOOD_ID
Parameter to specify the neighborhood predicate to use.
|
static OptionID |
AbstractDistanceBasedSpatialOutlier.NON_SPATIAL_DISTANCE_FUNCTION_ID
Parameter to specify the non spatial distance function to use
|
static OptionID |
TrimmedMeanApproach.Parameterizer.P_ID
Parameter for the percentile value p.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer.DISTANCEFUNCTION_ID
Parameter to specify the distance function to use
|
static OptionID |
PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer.K_ID
Parameter k
|
static OptionID |
ExternalNeighborhood.NEIGHBORHOOD_FILE_ID
Parameter to specify the neighborhood file
|
static OptionID |
ExtendedNeighborhood.Factory.Parameterizer.NEIGHBORHOOD_ID
Parameter to specify the neighborhood predicate to use.
|
static OptionID |
ExtendedNeighborhood.Factory.Parameterizer.STEPS_ID
Parameter to specify the number of steps allowed
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
UnweightedNeighborhoodAdapter.Factory.Parameterizer.INNER_ID
The parameter to give the non-weighted neighborhood to use.
|
static OptionID |
LinearWeightedExtendedNeighborhood.Factory.Parameterizer.NEIGHBORHOOD_ID
Parameter to specify the neighborhood predicate to use.
|
static OptionID |
LinearWeightedExtendedNeighborhood.Factory.Parameterizer.STEPS_ID
Parameter to specify the number of steps allowed
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
OutRankS1.Parameterizer.ALGORITHM_ID
Clustering algorithm to use.
|
static OptionID |
SOD.Parameterizer.ALPHA_ID
Parameter to indicate the multiplier for the discriminance value for
discerning small from large variances.
|
static OptionID |
OutRankS1.Parameterizer.ALPHA_ID
Alpha parameter for S1
|
static OptionID |
OUTRES.Parameterizer.D_ID
Option ID for Epsilon parameter
|
static OptionID |
AbstractAggarwalYuOutlier.Parameterizer.K_ID
OptionID for the target dimensionality.
|
static OptionID |
SOD.Parameterizer.KNN_ID
Parameter to specify the number of shared nearest neighbors to be
considered for learning the subspace properties., must be an integer
greater than 0.
|
static OptionID |
AggarwalYuEvolutionary.Parameterizer.M_ID
Parameter to specify the number of solutions must be an integer greater
than 1.
|
static OptionID |
SOD.Parameterizer.MODELS_ID
Parameter for keeping the models.
|
static OptionID |
AbstractAggarwalYuOutlier.Parameterizer.PHI_ID
OptionID for the grid size.
|
static OptionID |
AggarwalYuEvolutionary.Parameterizer.SEED_ID
Parameter to specify the random generator seed.
|
static OptionID |
SOD.Parameterizer.SIM_ID
Parameter for the similarity function.
|
Modifier and Type | Field and Description |
---|---|
private static OptionID |
LibSVMOneClassOutlierDetection.Parameterizer.KERNEL_ID
Parameter for kernel function.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
TrivialGeneratedOutlier.Parameterizer.EXPECT_ID
Expected share of outliers
|
static OptionID |
ByLabelOutlier.Parameterizer.OUTLIER_PATTERN_ID
The pattern to match outliers with.
|
Modifier and Type | Field and Description |
---|---|
private static OptionID |
EstimateIntrinsicDimensionality.Parameterizer.ESTIMATOR_ID
Estimation method
|
static OptionID |
DistanceStatisticsWithClasses.EXACT_ID
Flag to compute exact value range for binning.
|
static OptionID |
DistanceStatisticsWithClasses.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
EvaluateRankingQuality.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
RankingQualityHistogram.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.INCLUDESELF_ID
Parameter to include the query object.
|
static OptionID |
EvaluateRetrievalPerformance.Parameterizer.INCLUDESELF_ID
Parameter to include the query object.
|
private static OptionID |
AveragePrecisionAtK.Parameterizer.K_ID
Parameter k to compute the average precision at.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.K_ID
Parameter for k.
|
private static OptionID |
EstimateIntrinsicDimensionality.Parameterizer.KRATE_ID
Number of kNN to use for each object.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.MAXIMA_ID
Parameter for maximum.
|
static OptionID |
EvaluateRetrievalPerformance.Parameterizer.MAXK_ID
Parameter for maximum value of k.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.MINIMA_ID
Parameter for minimum.
|
static OptionID |
AddSingleScale.Parameterizer.MINMAX_ID
Minimum and maximum values.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.REP_ID
Parameter to specify the number of repetitions of computing the hopkins
value.
|
private static OptionID |
EstimateIntrinsicDimensionality.Parameterizer.SAMPLES_ID
Number of samples to draw from the data set.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.SAMPLESIZE_ID
Sample size.
|
static OptionID |
DistanceStatisticsWithClasses.SAMPLING_ID
Flag to enable sampling.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.SAMPLING_ID
Parameter to enable sampling.
|
static OptionID |
EvaluateRetrievalPerformance.Parameterizer.SAMPLING_ID
Parameter to enable sampling.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.SEED_ID
Parameter to control the sampling random seed.
|
static OptionID |
EvaluateRetrievalPerformance.Parameterizer.SEED_ID
Parameter to control the sampling random seed.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.SEED_ID
Parameter to specify the random generator seed.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractApplication.Parameterizer.DEBUG_ID
Optional Parameter to specify a class to enable debugging for.
|
static OptionID |
AbstractApplication.Parameterizer.DESCRIPTION_ID
Optional Parameter to specify a class to obtain a description for.
|
static OptionID |
AbstractApplication.Parameterizer.HELP_ID
Flag to obtain help-message.
|
static OptionID |
AbstractApplication.Parameterizer.HELP_LONG_ID
Flag to obtain help-message.
|
static OptionID |
ClassifierHoldoutEvaluationTask.Parameterizer.HOLDOUT_ID
Parameter to specify the holdout for evaluation, must extend
Holdout . |
static OptionID |
AbstractApplication.Parameterizer.INPUT_ID
Parameter that specifies the name of the input file.
|
static OptionID |
AbstractApplication.Parameterizer.OUTPUT_ID
Parameter that specifies the name of the output file.
|
static OptionID |
AbstractApplication.Parameterizer.VERBOSE_ID
Flag to allow verbose messages while running the application.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CacheDoubleDistanceKNNLists.Parameterizer.CACHE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceRangeQueries.Parameterizer.CACHE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceInOnDiskMatrix.Parameterizer.CACHE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceKNNLists.Parameterizer.DISTANCE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceRangeQueries.Parameterizer.DISTANCE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceInOnDiskMatrix.Parameterizer.DISTANCE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceKNNLists.Parameterizer.K_ID
Parameter that specifies the number of neighbors to precompute.
|
static OptionID |
CacheDoubleDistanceRangeQueries.Parameterizer.RADIUS_ID
Parameter that specifies the query radius to precompute.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.AGGREGATE_ID
Aggregation method.
|
static OptionID |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.DIM_ID
Dimensionality.
|
static OptionID |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.FORMAT_ID
Output format.
|
static OptionID |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.MAXK_ID
Final neighborhood size.
|
static OptionID |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.SAMPLE_ID
Samples size.
|
static OptionID |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.SEED_ID
Random seed.
|
static OptionID |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.STARTK_ID
Initial neighborhood size.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
VisualizeGeodesicDistances.Parameterizer.MODE_ID
Visualization mode.
|
static OptionID |
VisualizeGeodesicDistances.Parameterizer.RESOLUTION_ID
Image resolution.
|
static OptionID |
VisualizeGeodesicDistances.Parameterizer.STEPS_ID
Number of steps in the distance map.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.DISBALE_ID
Option ID for disabling methods.
|
static OptionID |
GreedyEnsembleExperiment.Parameterizer.DISTANCE_ID
Similarity measure
|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.MAXK_ID
Option ID for k step size.
|
static OptionID |
EvaluatePrecomputedOutlierScores.Parameterizer.NAME_ID
Row name.
|
static OptionID |
GreedyEnsembleExperiment.Parameterizer.PRESCALING_ID
Scaling to apply to input scores.
|
static OptionID |
GreedyEnsembleExperiment.Parameterizer.RATE_ID
Expected rate of outliers
|
static OptionID |
EvaluatePrecomputedOutlierScores.Parameterizer.REVERSED_ID
Pattern for reversed methods.
|
static OptionID |
GreedyEnsembleExperiment.Parameterizer.SCALING_ID
Scaling to apply to ensemble scores.
|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.SCALING_ID
Option ID for scaling class.
|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.STARTK_ID
Option ID for k start size.
|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.STEPK_ID
Option ID for k step size.
|
static OptionID |
GreedyEnsembleExperiment.Parameterizer.VOTING_ID
Ensemble voting function.
|
Modifier and Type | Method and Description |
---|---|
int |
DocumentParameters.SortByOption.compare(OptionID o1,
OptionID o2) |
Modifier and Type | Method and Description |
---|---|
private static void |
DocumentParameters.buildParameterIndex(Map<Class<?>,List<Parameter<?>>> byclass,
Map<OptionID,List<Pair<Parameter<?>,Class<?>>>> byopt) |
private static Document |
DocumentParameters.makeByOptOverviewHTML(Map<OptionID,List<Pair<Parameter<?>,Class<?>>>> byopt) |
private static void |
DocumentParameters.makeByOptOverviewWiki(Map<OptionID,List<Pair<Parameter<?>,Class<?>>>> byopt,
DocumentParameters.WikiStream out) |
Modifier and Type | Field and Description |
---|---|
static OptionID |
JSONResultHandler.Parameterizer.PORT_ID
Port to use for listening
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
RandomProjection.Parameterizer.DIMENSIONALITY_ID
Parameter for the desired output dimensionality.
|
static OptionID |
RandomProjection.Parameterizer.FAMILY_ID
Parameter for the projection family.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
SimpleGaussianUncertainifier.Parameterizer.DEV_MAX_ID
Parameter for maximum 3-sigma deviation.
|
static OptionID |
UniformUncertainifier.Parameterizer.DEV_MAX_ID
Maximum deviation of the generated bounding box.
|
static OptionID |
SimpleGaussianUncertainifier.Parameterizer.DEV_MIN_ID
Parameter for minimum 3-sigma deviation.
|
static OptionID |
UniformUncertainifier.Parameterizer.DEV_MIN_ID
Minimum deviation of the generated bounding box.
|
static OptionID |
AbstractDiscreteUncertainifier.Parameterizer.INNER_ID
Class to use for generating the uncertain instances.
|
static OptionID |
AbstractDiscreteUncertainifier.Parameterizer.MULT_MAX_ID
Maximum quantity of generated samples.
|
static OptionID |
AbstractDiscreteUncertainifier.Parameterizer.MULT_MIN_ID
Minimum quantity of generated samples.
|
static OptionID |
Uncertainifier.SYMMETRIC_ID
Shared parameter: to force centering the uncertain region on the exact
vector.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractDatabase.Parameterizer.DATABASE_CONNECTION_ID
Option to specify the data source for the database.
|
static OptionID |
AbstractDatabase.Parameterizer.INDEX_ID
Parameter to specify the indexes to use.
|
Modifier and Type | Field and Description |
---|---|
private static OptionID |
BundleDatabaseConnection.Parameterizer.BUNDLE_ID
Option ID for the bundle parameter.
|
static OptionID |
GeneratorXMLDatabaseConnection.CONFIGFILE_ID
Parameter to give the configuration file
|
static OptionID |
DBIDRangeDatabaseConnection.Parameterizer.COUNT_ID
Parameter for number of IDs to generate
|
static OptionID |
RandomDoubleVectorDatabaseConnection.Parameterizer.DIM_ID
Database to specify the random vector dimensionality.
|
static OptionID |
AbstractDatabaseConnection.Parameterizer.FILTERS_ID
Filters to apply to the input data.
|
static OptionID |
FileBasedDatabaseConnection.Parameterizer.INPUT_ID
Parameter that specifies the name of the input file to be parsed.
|
static OptionID |
AbstractDatabaseConnection.Parameterizer.PARSER_ID
Parameter to specify the parser to provide a database.
|
static OptionID |
GeneratorXMLDatabaseConnection.RANDOMSEED_ID
Parameter to give the configuration file
|
static OptionID |
RandomDoubleVectorDatabaseConnection.Parameterizer.SEED_ID
Random generator seed.
|
static OptionID |
RandomDoubleVectorDatabaseConnection.Parameterizer.SIZE_ID
Parameter to specify the database size to generate.
|
static OptionID |
GeneratorXMLDatabaseConnection.SIZE_SCALE_ID
Parameter to give the configuration file
|
static OptionID |
ExternalIDJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
static OptionID |
PresortedBlindJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
static OptionID |
LabelJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
static OptionID |
DBIDRangeDatabaseConnection.Parameterizer.START_ID
Parameter for starting ID to generate
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
FixedDBIDsFilter.Parameterizer.IDSTART_ID
Optional parameter to specify the first object ID to use.
|
Modifier and Type | Field and Description |
---|---|
private static OptionID |
VectorDimensionalityFilter.Parameterizer.DIM_P
Parameter for specifying the dimensionality.
|
static OptionID |
ReplaceNaNWithRandomFilter.Parameterizer.REPLACEMENT_DISTRIBUTION
Parameter to specify the distribution to sample replacement values from.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AttributeWiseBetaNormalization.Parameterizer.ALPHA_ID
Shape parameter.
|
static OptionID |
AttributeWiseCDFNormalization.Parameterizer.DISTRIBUTIONS_ID
Parameter for distribution estimators.
|
static OptionID |
AttributeWiseBetaNormalization.Parameterizer.DISTRIBUTIONS_ID
Parameter for distribution estimators.
|
static OptionID |
AttributeWiseMinMaxNormalization.Parameterizer.MAXIMA_ID
Parameter for maximum.
|
static OptionID |
AttributeWiseVarianceNormalization.Parameterizer.MEAN_ID
Parameter for means.
|
static OptionID |
AttributeWiseMinMaxNormalization.Parameterizer.MINIMA_ID
Parameter for minimum.
|
static OptionID |
AttributeWiseVarianceNormalization.Parameterizer.STDDEV_ID
Parameter for stddevs.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
Log1PlusNormalization.Parameterizer.BOOST_ID
Boosting factor parameter.
|
static OptionID |
InstanceMinMaxNormalization.Parameterizer.MAX_ID
Option ID for maximum value.
|
static OptionID |
InstanceMinMaxNormalization.Parameterizer.MIN_ID
Option ID for minimum value.
|
static OptionID |
LengthNormalization.Parameterizer.NORM_ID
Option ID for normalization norm.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ByLabelFilter.Parameterizer.LABELFILTER_PATTERN_ID
Parameter that specifies the filter pattern (regular expression).
|
static OptionID |
ByLabelFilter.Parameterizer.LABELFILTER_PATTERN_INVERT_ID
Flag to use the pattern in inverted mode
Key:
-patternfilter.invert
|
private static OptionID |
RandomSamplingStreamFilter.Parameterizer.PROB_ID
Option ID for sampling probability
|
static OptionID |
ShuffleObjectsFilter.Parameterizer.SEED_ID
Optional parameter to specify a seed for randomly shuffling the rows of
the database.
|
private static OptionID |
RandomSamplingStreamFilter.Parameterizer.SEED_ID
Option ID for random seed
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ClassicMultidimensionalScalingTransform.Parameterizer.DIM_ID
Desired dimensionality.
|
static OptionID |
ClassicMultidimensionalScalingTransform.Parameterizer.DISTANCE_ID
Distant metric.
|
static OptionID |
GlobalPrincipalComponentAnalysisTransform.Parameterizer.FILTER_ID
To specify the eigenvectors to keep.
|
static OptionID |
HistogramJitterFilter.Parameterizer.JITTER_ID
Option ID for the jitter strength.
|
static OptionID |
PerturbationFilter.Parameterizer.MAXIMA_ID
Parameter for maximum.
|
static OptionID |
PerturbationFilter.Parameterizer.MINIMA_ID
Parameter for minimum.
|
static OptionID |
PerturbationFilter.Parameterizer.NOISEDISTRIBUTION_ID
Parameter for selecting the noise distribution.
|
static OptionID |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.NUMBER_SELECTED_ATTRIBUTES_ID
Parameter for the desired cardinality of the subset of attributes
selected for projection.
|
static OptionID |
AbstractSupervisedProjectionVectorFilter.Parameterizer.P_ID
The number of dimensions to keep.
|
static OptionID |
PerturbationFilter.Parameterizer.PERCENTAGE_ID
Optional parameter to specify a percentage of the standard deviation of
the random Gaussian noise generation, given the standard deviation of the
corresponding attribute in the original data distribution (assuming a
Gaussian there).
|
static OptionID |
ProjectionFilter.Parameterizer.PROJ_ID
Parameter to specify the projection to use
Key:
-projection
|
static OptionID |
PerturbationFilter.Parameterizer.SCALINGREFERENCE_ID
Parameter for selecting scaling reference.
|
static OptionID |
HistogramJitterFilter.Parameterizer.SEED_ID
Option ID for the jitter random seed.
|
static OptionID |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.SEED_ID
Optional parameter to specify a seed for random projection.
|
static OptionID |
PerturbationFilter.Parameterizer.SEED_ID
Optional parameter to specify a seed for random Gaussian noise
generation.
|
static OptionID |
NumberVectorFeatureSelectionFilter.Parameterizer.SELECTED_ATTRIBUTES_ID
Selected attributes parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ClassLabelFilter.Parameterizer.CLASS_LABEL_CLASS_ID
Parameter to specify the class of occurring class labels.
|
static OptionID |
ClassLabelFilter.Parameterizer.CLASS_LABEL_INDEX_ID
Optional parameter that specifies the index of the label to be used as
class label, must be an integer equal to or greater than 0.
|
static OptionID |
UncertainSplitFilter.Parameterizer.DIM_ID
Parameter for specifying the number of dimensions of the sample.
|
static OptionID |
ExternalIDFilter.Parameterizer.EXTERNALID_INDEX_ID
Parameter that specifies the index of the label to be used as external
Id, starting at 0.
|
static OptionID |
UncertainifyFilter.Parameterizer.KEEP_ID
Flag to keep the original data.
|
static OptionID |
ClassLabelFromPatternFilter.Parameterizer.NEGATIVE_ID
Class label to assign to negative instances.
|
static OptionID |
ClassLabelFromPatternFilter.Parameterizer.PATTERN_ID
Pattern for recognizing positive objects.
|
static OptionID |
ClassLabelFromPatternFilter.Parameterizer.POSITIVE_ID
Class label to assign to positive instances.
|
static OptionID |
UncertainifyFilter.Parameterizer.SEED_ID
Seed for random generation.
|
static OptionID |
SplitNumberVectorFilter.Parameterizer.SELECTED_ATTRIBUTES_ID
The parameter listing the split dimensions.
|
static OptionID |
UncertainifyFilter.Parameterizer.UNCERTAINITY_MODEL_ID
Parameter to specify the uncertainityModel used for the
uncertainification.
|
static OptionID |
MultivariateTimeSeriesFilter.Parameterizer.VARIATES_ID
Parameter for specifying the number of variates of this series.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CSVReaderFormat.Parameterizer.COLUMN_SEPARATOR_ID
OptionID for the column separator parameter (defaults to whitespace as in
CSVReaderFormat.DEFAULT_SEPARATOR . |
static OptionID |
CSVReaderFormat.Parameterizer.COMMENT_ID
Comment pattern.
|
static OptionID |
NumberVectorLabelParser.Parameterizer.LABEL_INDICES_ID
A comma separated list of the indices of labels (may be numeric),
counting whitespace separated entries in a line starting with 0.
|
static OptionID |
ArffParser.Parameterizer.MAGIC_CLASS_ID
Pattern for recognizing class label attributes.
|
static OptionID |
ArffParser.Parameterizer.MAGIC_EID_ID
Pattern for recognizing external ID attributes.
|
static OptionID |
TermFrequencyParser.Parameterizer.NORMALIZE_FLAG
Option ID for normalization.
|
static OptionID |
CSVReaderFormat.Parameterizer.QUOTE_ID
OptionID for the quote character parameter (defaults to a double
quotation mark as in
CSVReaderFormat.QUOTE_CHARS . |
static OptionID |
StringParser.Parameterizer.TRIM_ID
Flag to trim whitespace.
|
static OptionID |
NumberVectorLabelParser.Parameterizer.VECTOR_TYPE_ID
Parameter to specify the type of vectors to produce.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
IndexBasedDistanceFunction.INDEX_ID
OptionID for the index parameter
|
static OptionID |
WeightedNumberVectorDistanceFunction.WEIGHTS_ID
Parameter to set the weights of the weighted distance function.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractSimilarityAdapter.Parameterizer.SIMILARITY_FUNCTION_ID
Parameter to specify the similarity function to derive the distance
between database objects from.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
HSBHistogramQuadraticDistanceFunction.BPP_ID
Parameter for the kernel dimensionality.
|
static OptionID |
RGBHistogramQuadraticDistanceFunction.BPP_ID
Parameter for the kernel dimensionality.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
DiskCacheBasedDoubleDistanceFunction.Parameterizer.MATRIX_ID
Parameter that specifies the name of the distance matrix file.
|
static OptionID |
FileBasedDoubleDistanceFunction.Parameterizer.MATRIX_ID
Parameter that specifies the name of the distance matrix file.
|
static OptionID |
FileBasedDoubleDistanceFunction.Parameterizer.PARSER_ID
Optional parameter to specify the parsers to provide a database, must
extend
DistanceParser . |
Modifier and Type | Field and Description |
---|---|
static OptionID |
DimensionSelectingLatLngDistanceFunction.Parameterizer.LATDIM_ID
Latitude dimension parameter.
|
static OptionID |
DimensionSelectingLatLngDistanceFunction.Parameterizer.LNGDIM_ID
Longitude dimension parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
LPNormDistanceFunction.Parameterizer.P_ID
OptionID for the "p" parameter
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
OnedimensionalDistanceFunction.Parameterizer.DIM_ID
Parameter for dimensionality.
|
static OptionID |
AbstractDimensionsSelectingDistanceFunction.Parameterizer.DIMS_ID
Dimensions parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractEditDistanceFunction.Parameterizer.BANDSIZE_ID
Bandsize parameter.
|
static OptionID |
EDRDistanceFunction.Parameterizer.DELTA_ID
DELTA parameter
|
static OptionID |
ERPDistanceFunction.Parameterizer.G_ID
G parameter
|
static OptionID |
LCSSDistanceFunction.Parameterizer.PDELTA_ID
PDELTA parameter
|
static OptionID |
LCSSDistanceFunction.Parameterizer.PEPSILON_ID
PEPSILON parameter
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
InvertedDistanceSimilarityFunction.DISTANCE_FUNCTION_ID
Parameter to specify the similarity function to derive the distance between
database objects from.
|
static OptionID |
AbstractIndexBasedSimilarityFunction.INDEX_ID
Parameter to specify the preprocessor to be used.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PolynomialKernelFunction.Parameterizer.BIAS_ID
Bias parameter.
|
static OptionID |
SigmoidKernelFunction.Parameterizer.C_ID
C parameter: scaling
|
static OptionID |
RationalQuadraticKernelFunction.Parameterizer.C_ID
C parameter
|
static OptionID |
PolynomialKernelFunction.Parameterizer.DEGREE_ID
Degree parameter.
|
static OptionID |
LaplaceKernelFunction.Parameterizer.SIGMA_ID
Sigma parameter: standard deviation.
|
static OptionID |
RadialBasisFunctionKernelFunction.Parameterizer.SIGMA_ID
Sigma parameter: standard deviation.
|
static OptionID |
SigmoidKernelFunction.Parameterizer.THETA_ID
Theta parameter: bias
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
DisjointCrossValidation.Parameterizer.NFOLD_ID
Parameter for number of folds.
|
static OptionID |
RandomizedCrossValidation.Parameterizer.NFOLD_ID
Parameter for number of folds.
|
static OptionID |
StratifiedCrossValidation.Parameterizer.NFOLD_ID
Parameter for number of folds.
|
static OptionID |
RandomizedHoldout.Parameterizer.SEED_ID
Random seeding for holdout evaluation.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
EvaluateClustering.NOISE_ID
Parameter flag for special noise handling.
|
static OptionID |
EvaluateClustering.REFERENCE_ID
Parameter to obtain the reference clustering.
|
static OptionID |
EvaluateClustering.SELFPAIR_ID
Parameter flag to disable self-pairing
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
EvaluateConcordantPairs.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateDaviesBouldin.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateSquaredErrors.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluatePBMIndex.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateCIndex.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateSilhouette.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateVarianceRatioCriteria.Parameterizer.NO_PENALIZE_ID
Do not penalize ignored noise.
|
static OptionID |
EvaluateSilhouette.Parameterizer.NO_PENALIZE_ID
Do not penalize ignored noise.
|
static OptionID |
EvaluateVarianceRatioCriteria.Parameterizer.NOISE_ID
Parameter for the option, how noise should be treated.
|
static OptionID |
EvaluateConcordantPairs.Parameterizer.NOISE_ID
Parameter for the option, how noise should be treated.
|
static OptionID |
EvaluateDaviesBouldin.Parameterizer.NOISE_ID
Parameter for the option, how noise should be treated.
|
static OptionID |
EvaluateSquaredErrors.Parameterizer.NOISE_ID
Parameter to treat noise as a single cluster.
|
static OptionID |
EvaluatePBMIndex.Parameterizer.NOISE_ID
Parameter for the option, how noise should be treated.
|
static OptionID |
EvaluateCIndex.Parameterizer.NOISE_ID
Parameter for the option, how noise should be treated.
|
static OptionID |
EvaluateSilhouette.Parameterizer.NOISE_ID
Parameter to treat noise as a single cluster.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ComputeOutlierHistogram.BINS_ID
number of bins for the histogram
Default value:
EuclideanDistanceFunction
Key: -comphist.bins
|
static OptionID |
ComputeOutlierHistogram.POSITIVE_CLASS_NAME_ID
The object pattern to identify positive classes
Key:
-comphist.positive
|
static OptionID |
ComputeOutlierHistogram.SCALING_ID
Parameter to specify a scaling function to use.
|
static OptionID |
ComputeOutlierHistogram.SPLITFREQ_ID
Flag to count frequencies of outliers and non-outliers separately
Key:
-histogram.splitfreq
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
OutlierPrecisionAtKCurve.Parameterizer.MAX_K_ID
Maximum value for k
Key:
-precision.k
|
static OptionID |
OutlierROCCurve.Parameterizer.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
OutlierRankingEvaluation.Parameterizer.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
JudgeOutlierScores.POSITIVE_CLASS_NAME_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
OutlierPrecisionRecallCurve.Parameterizer.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
OutlierPrecisionAtKCurve.Parameterizer.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
OutlierThresholdClustering.Parameterizer.SCALING_ID
Parameter to specify a scaling function to use.
|
static OptionID |
JudgeOutlierScores.SCALING_ID
Parameter to specify a scaling function to use.
|
static OptionID |
OutlierThresholdClustering.Parameterizer.THRESHOLD_ID
Parameter to specify the threshold
Key:
-thresholdclust.threshold
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PrecisionAtKEvaluation.Parameterizer.K_ID
Option ID for the k parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ComputeSimilarityMatrixImage.SCALING_ID
OptionID for the scaling function to use
|
static OptionID |
ComputeSimilarityMatrixImage.SKIPZERO_ID
OptionID to skip zero values when plotting to increase contrast.
|
Modifier and Type | Field and Description |
---|---|
protected static OptionID |
DynamicParameters.REMAINING_OPTIONS_ID
OptionID for unrecognized options.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PagedIndexFactory.Parameterizer.PAGEFILE_ID
Optional parameter that specifies the factory type of pagefile to use for
the index.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PrecomputedDistanceMatrix.Factory.Parameterizer.DISTANCE_ID
Option parameter for the precomputed distance matrix.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
InMemoryIDistanceIndex.Factory.Parameterizer.DISTANCE_ID
Parameter for the distance function
|
static OptionID |
InMemoryIDistanceIndex.Factory.Parameterizer.K_ID
Number of reference points.
|
static OptionID |
InMemoryIDistanceIndex.Factory.Parameterizer.REFERENCE_ID
Initialization method.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
InMemoryLSHIndex.Parameterizer.BUCKETS_ID
Number of hash tables to use for LSH.
|
static OptionID |
InMemoryLSHIndex.Parameterizer.FAMILY_ID
Hash function family parameter.
|
static OptionID |
InMemoryLSHIndex.Parameterizer.L_ID
Number of hash tables to use for LSH.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CosineHashFunctionFamily.Parameterizer.NUMPROJ_ID
Number of projections to use in each hash function.
|
static OptionID |
AbstractProjectedHashFunctionFamily.Parameterizer.NUMPROJ_ID
Number of projections to use in each hash function.
|
static OptionID |
CosineHashFunctionFamily.Parameterizer.RANDOM_ID
Parameter for fixing the random seed.
|
static OptionID |
AbstractProjectedHashFunctionFamily.Parameterizer.RANDOM_ID
Parameter for fixing the random seed.
|
static OptionID |
AbstractProjectedHashFunctionFamily.Parameterizer.WIDTH_ID
Parameter for choosing the bin width.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
RandomProjectedNeighborssAndDensities.Parameterizer.RANDOM_ID
Random seed parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CachedDoubleDistanceKNNPreprocessor.Factory.Parameterizer.CACHE_ID
Option ID for the kNN file.
|
static OptionID |
SpacefillingKNNPreprocessor.Factory.Parameterizer.CURVES_ID
Parameter for choosing the space filling curves to use.
|
static OptionID |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.CURVES_ID
Parameter for choosing the space filling curves to use.
|
static OptionID |
SpacefillingKNNPreprocessor.Factory.Parameterizer.DIM_ID
Parameter for choosing the number of dimensions to use for each curve.
|
static OptionID |
AbstractMaterializeKNNPreprocessor.Factory.DISTANCE_FUNCTION_ID
Parameter to indicate the distance function to be used to ascertain the
nearest neighbors.
|
static OptionID |
AbstractMaterializeKNNPreprocessor.Factory.K_ID
Parameter to specify the number of nearest neighbors of an object to be
materialized. must be an integer greater than 1.
|
static OptionID |
PartitionApproximationMaterializeKNNPreprocessor.Factory.Parameterizer.PARTITIONS_ID
Parameter to specify the number of partitions to use for materializing
the kNN.
|
static OptionID |
SpacefillingKNNPreprocessor.Factory.Parameterizer.PROJECTION_ID
Parameter for choosing the random projections.
|
static OptionID |
NaiveProjectedKNNPreprocessor.Factory.Parameterizer.PROJECTION_ID
Parameter for choosing the random projections.
|
static OptionID |
NaiveProjectedKNNPreprocessor.Factory.Parameterizer.PROJECTIONS_ID
Parameter for choosing the number of projections to use.
|
static OptionID |
SpacefillingKNNPreprocessor.Factory.Parameterizer.RANDOM_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.RANDOM_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
NaiveProjectedKNNPreprocessor.Factory.Parameterizer.RANDOM_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
RandomSampleKNNPreprocessor.Factory.Parameterizer.SEED_ID
Random number generator seed.
|
static OptionID |
PartitionApproximationMaterializeKNNPreprocessor.Factory.Parameterizer.SEED_ID
Parameter to specify the random number generator.
|
static OptionID |
RandomSampleKNNPreprocessor.Factory.Parameterizer.SHARE_ID
Parameter to specify how many objects to consider for computing the
kNN.
|
static OptionID |
SpacefillingKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
SpacefillingKNNPreprocessor.Factory.Parameterizer.WINDOW_ID
Parameter for setting the widows size multiplicator.
|
static OptionID |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.WINDOW_ID
Parameter for setting the widows size multiplicator.
|
static OptionID |
NaiveProjectedKNNPreprocessor.Factory.Parameterizer.WINDOW_ID
Parameter for setting the widows size multiplicator.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
KNNQueryFilteredPCAIndex.Factory.Parameterizer.K_ID
Optional parameter to specify the number of nearest neighbors
considered in the PCA, must be an integer greater than 0.
|
static OptionID |
AbstractFilteredPCAIndex.Factory.PCA_DISTANCE_ID
Parameter to specify the distance function used for running PCA.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
HiSCPreferenceVectorIndex.Factory.ALPHA_ID
The maximum absolute variance along a coordinate axis.
|
static OptionID |
DiSHPreferenceVectorIndex.Factory.EPSILON_ID
A comma separated list of positive doubles specifying the maximum radius
of the neighborhood to be considered in each dimension for determination
of the preference vector (default is
DiSHPreferenceVectorIndex.Factory.DEFAULT_EPSILON in each
dimension). |
static OptionID |
HiSCPreferenceVectorIndex.Factory.K_ID
The number of nearest neighbors considered to determine the preference
vector.
|
static OptionID |
DiSHPreferenceVectorIndex.Factory.MINPTS_ID
Positive threshold for minimum numbers of points in the
epsilon-neighborhood of a point, must satisfy following
DiSHPreferenceVectorIndex.Factory.CONDITION . |
static OptionID |
DiSHPreferenceVectorIndex.Factory.STRATEGY_ID
The strategy for determination of the preference vector, available
strategies are:
DiSHPreferenceVectorIndex.Strategy.APRIORI and
DiSHPreferenceVectorIndex.Strategy.MAX_INTERSECTION . |
Modifier and Type | Field and Description |
---|---|
static OptionID |
SharedNearestNeighborPreprocessor.Factory.DISTANCE_FUNCTION_ID
Parameter to indicate the distance function to be used to ascertain the
nearest neighbors.
|
static OptionID |
SharedNearestNeighborPreprocessor.Factory.NUMBER_OF_NEIGHBORS_ID
Parameter to indicate the number of neighbors to be taken into account
for the shared-nearest-neighbor similarity.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ProjectedIndex.Factory.Parameterizer.DISABLE_REFINE_FLAG
Option ID for disabling refinement.
|
static OptionID |
PINN.Parameterizer.H_ID
Neighborhood size.
|
static OptionID |
ProjectedIndex.Factory.Parameterizer.INDEX_ID
Option ID for the inner index to use.
|
static OptionID |
ProjectedIndex.Factory.Parameterizer.K_MULTIPLIER_ID
Option ID for querying a larger k.
|
static OptionID |
ProjectedIndex.Factory.Parameterizer.MATERIALIZE_FLAG
Option ID for materialization.
|
static OptionID |
ProjectedIndex.Factory.Parameterizer.PROJ_ID
Option ID for the projection to use.
|
static OptionID |
PINN.Parameterizer.RANDOM_ID
Random generator.
|
static OptionID |
PINN.Parameterizer.S_ID
Sparsity option.
|
static OptionID |
PINN.Parameterizer.T_ID
Target dimensionality.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractCoverTree.Factory.Parameterizer.DISTANCE_FUNCTION_ID
Parameter to specify the distance function to determine the distance
between database objects, must extend
DistanceFunction . |
static OptionID |
AbstractCoverTree.Factory.Parameterizer.EXPANSION_ID
Expansion rate of the tree (going upward).
|
static OptionID |
AbstractCoverTree.Factory.Parameterizer.TRUNCATE_ID
Truncate branches when they have less than this number of instances.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractMTreeFactory.Parameterizer.DISTANCE_FUNCTION_ID
Parameter to specify the distance function to determine the distance
between database objects, must extend
DistanceFunction . |
static OptionID |
AbstractMTreeFactory.Parameterizer.INSERT_STRATEGY_ID
Parameter to specify the insertion strategy to construct the tree.
|
static OptionID |
AbstractMTreeFactory.Parameterizer.SPLIT_STRATEGY_ID
Parameter to specify the splitting strategy to construct the tree.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractMkTreeUnifiedFactory.Parameterizer.K_MAX_ID
Parameter specifying the maximal number k of reverse k nearest neighbors
to be supported, must be an integer greater than 0.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
MkAppTreeFactory.K_ID
Parameter for k
|
static OptionID |
MkAppTreeFactory.NOLOG_ID
Parameter for nolog
|
static OptionID |
MkAppTreeFactory.P_ID
Parameter for p
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
MkCopTreeFactory.K_ID
Parameter for k
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
RandomSplit.Parameterizer.RANDOM_ID
Option ID for the random generator.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
MinimalisticMemoryKDTree.Factory.Parameterizer.LEAFSIZE_P
Option for setting the maximum leaf size.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractRStarTreeFactory.Parameterizer.BULK_SPLIT_ID
Parameter for bulk strategy
|
static OptionID |
AbstractRStarTreeFactory.Parameterizer.INSERTION_STRATEGY_ID
Fast-insertion parameter.
|
static OptionID |
AbstractRStarTreeFactory.Parameterizer.MINIMUM_FILL_ID
Parameter for the relative minimum fill.
|
static OptionID |
AbstractRStarTreeFactory.Parameterizer.OVERFLOW_STRATEGY_ID
Overflow treatment.
|
static OptionID |
AbstractRStarTreeFactory.Parameterizer.SPLIT_STRATEGY_ID
Split strategy parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
RdKNNTreeFactory.DISTANCE_FUNCTION_ID
Parameter for distance function
|
static OptionID |
RdKNNTreeFactory.K_ID
Parameter for k
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
SpatialSortBulkSplit.Parameterizer.SORTER_ID
Option ID for spatial sorting
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CombinedInsertionStrategy.Parameterizer.DIR_STRATEGY_ID
Insertion strategy for directory nodes.
|
static OptionID |
ApproximativeLeastOverlapInsertionStrategy.Parameterizer.INSERTION_CANDIDATES_ID
Fast-insertion parameter.
|
static OptionID |
CombinedInsertionStrategy.Parameterizer.LEAF_STRATEGY_ID
Insertion strategy for leaf nodes.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
LimitedReinsertOverflowTreatment.Parameterizer.REINSERT_STRATEGY_ID
Fast-insertion parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractPartialReinsert.Parameterizer.REINSERT_AMOUNT_ID
Reinsertion share
|
static OptionID |
AbstractPartialReinsert.Parameterizer.REINSERT_DISTANCE_ID
Reinsertion share
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PartialVAFile.Factory.PARTITIONS_ID
Number of partitions to use in each dimension.
|
static OptionID |
VAFile.Factory.PARTITIONS_ID
Number of partitions to use in each dimension.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
EarthModel.MODEL_ID
Parameter to choose the earth model to use.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PercentageEigenPairFilter.ALPHA_ID
The threshold for 'strong' eigenvectors: the 'strong' eigenvectors explain
a portion of at least alpha of the total variance.
|
static OptionID |
PCAFilteredRunner.Parameterizer.BIG_ID
Parameter to specify a constant big value to reset high eigenvalues, must
be a double greater than 0.
|
static OptionID |
LimitEigenPairFilter.EIGENPAIR_FILTER_ABSOLUTE
"absolute" Flag
|
static OptionID |
CompositeEigenPairFilter.EIGENPAIR_FILTER_COMPOSITE_LIST
The list of filters to use.
|
static OptionID |
LimitEigenPairFilter.EIGENPAIR_FILTER_DELTA
Parameter delta
|
static OptionID |
FirstNEigenPairFilter.EIGENPAIR_FILTER_N
Paremeter n
|
static OptionID |
ProgressiveEigenPairFilter.EIGENPAIR_FILTER_PALPHA
Parameter progressive alpha.
|
static OptionID |
RelativeEigenPairFilter.EIGENPAIR_FILTER_RALPHA
Parameter relative alpha.
|
static OptionID |
WeakEigenPairFilter.EIGENPAIR_FILTER_WALPHA
OptionID for the weak alpha value of
WeakEigenPairFilter ,
ProgressiveEigenPairFilter
and
SignificantEigenPairFilter |
static OptionID |
RANSACCovarianceMatrixBuilder.Parameterizer.ITER_ID
Number of iterations.
|
static OptionID |
PCARunner.PCA_COVARIANCE_MATRIX
Parameter to specify the class to compute the covariance matrix, must be a
subclass of
CovarianceMatrixBuilder . |
static OptionID |
PCAFilteredRunner.Parameterizer.PCA_EIGENPAIR_FILTER
Parameter to specify the filter for determination of the strong and weak
eigenvectors, must be a subclass of
EigenPairFilter . |
static OptionID |
RANSACCovarianceMatrixBuilder.Parameterizer.SEED_ID
Random seed
|
static OptionID |
PCAFilteredRunner.Parameterizer.SMALL_ID
Parameter to specify a constant small value to reset low eigenvalues, must
be a double greater than 0.
|
static OptionID |
WeightedCovarianceMatrixBuilder.WEIGHT_ID
Parameter to specify the weight function to use in weighted PCA, must
implement
WeightFunction
. |
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractRandomProjectionFamily.Parameterizer.RANDOM_ID
Parameter for the random generator.
|
static OptionID |
AchlioptasRandomProjectionFamily.Parameterizer.SPARSITY_ID
Parameter for the projection sparsity.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
BetaDistribution.Parameterizer.ALPHA_ID
Alpha parameter.
|
static OptionID |
BetaDistribution.Parameterizer.BETA_ID
Beta parameter.
|
static OptionID |
ConstantDistribution.Parameterizer.CONSTANT_ID
Constant value parameter
|
static OptionID |
ChiSquaredDistribution.Parameterizer.DOF_ID
Degrees of freedom parameter.
|
static OptionID |
GammaDistribution.Parameterizer.K_ID
K parameter.
|
static OptionID |
AbstractDistribution.Parameterizer.LOCATION_ID
Location parameter.
|
static OptionID |
LogNormalDistribution.Parameterizer.LOGMEAN_ID
LogMean parameter
|
static OptionID |
LogNormalDistribution.Parameterizer.LOGSTDDEV_ID
LogScale parameter
|
static OptionID |
UniformDistribution.Parameterizer.MAX_ID
Maximum value
|
static OptionID |
UniformDistribution.Parameterizer.MIN_ID
Minimum value
|
static OptionID |
PoissonDistribution.Parameterizer.N_ID
Number of trials.
|
static OptionID |
StudentsTDistribution.Parameterizer.NU_ID
Degrees of freedom.
|
static OptionID |
PoissonDistribution.Parameterizer.PROB_ID
Success probability.
|
static OptionID |
AbstractDistribution.Parameterizer.RANDOM_ID
Parameter to specify the random seeding source.
|
static OptionID |
ExponentialDistribution.Parameterizer.RATE_ID
Shape parameter gamma.
|
static OptionID |
LaplaceDistribution.Parameterizer.RATE_ID
Shape parameter gamma.
|
static OptionID |
AbstractDistribution.Parameterizer.SCALE_ID
Scale parameter.
|
static OptionID |
CauchyDistribution.Parameterizer.SHAPE_ID
Shape parameter gamma.
|
static OptionID |
AbstractDistribution.Parameterizer.SHAPE_ID
Shape parameter.
|
static OptionID |
KappaDistribution.Parameterizer.SHAPE1_ID
First shape parameter.
|
static OptionID |
KappaDistribution.Parameterizer.SHAPE2_ID
Second shape parameter.
|
static OptionID |
LogGammaDistribution.Parameterizer.SHIFT_ID
Shifting offset parameter.
|
static OptionID |
LogGammaAlternateDistribution.Parameterizer.SHIFT_ID
Shifting offset parameter.
|
static OptionID |
LogNormalDistribution.Parameterizer.SHIFT_ID
Shift parameter
|
static OptionID |
SkewGeneralizedNormalDistribution.Parameterizer.SKEW_ID
Skew parameter
|
static OptionID |
GammaDistribution.Parameterizer.THETA_ID
Theta parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
TrimmedEstimator.Parameterizer.INNER_ID
Option for the class to use on the trimmed sample.
|
static OptionID |
WinsorisingEstimator.Parameterizer.INNER_ID
Option for the class to use on the winsorized sample.
|
static OptionID |
TrimmedEstimator.Parameterizer.TRIM_ID
Option for specifying the amount of data to trim.
|
static OptionID |
WinsorisingEstimator.Parameterizer.WINSORIZE_ID
Option for specifying the amount of data to winsorize.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
LRUCachePageFileFactory.Parameterizer.CACHE_SIZE_ID
Parameter to specify the size of the cache in bytes, must be an integer
equal to or greater than 0.
|
static OptionID |
PersistentPageFileFactory.Parameterizer.FILE_ID
Optional parameter that specifies the name of the file storing the index.
|
static OptionID |
OnDiskArrayPageFileFactory.Parameterizer.FILE_ID
Optional parameter that specifies the name of the file storing the index.
|
static OptionID |
AbstractPageFileFactory.Parameterizer.PAGE_SIZE_ID
Parameter to specify the size of a page in bytes, must be an integer
greater than 0.
|
static OptionID |
LRUCachePageFileFactory.Parameterizer.PAGEFILE_ID
Parameter to specify the inner pagefile.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ClusteringVectorDumper.Parameterizer.APPEND_ID
Append flag.
|
static OptionID |
KMLOutputHandler.Parameterizer.AUTOOPEN_ID
Parameter for automatically opening the output file.
|
static OptionID |
KMLOutputHandler.Parameterizer.COMPAT_ID
Parameter for compatibility mode.
|
static OptionID |
ResultWriter.Parameterizer.FILTER_PATTERN_ID
Pattern to filter the output
Key:
-out.filter
|
static OptionID |
ClusteringVectorDumper.Parameterizer.FORCE_LABEL_ID
Force label parameter.
|
static OptionID |
ResultWriter.Parameterizer.GZIP_OUTPUT_ID
Flag to control GZIP compression.
|
static OptionID |
ClusteringVectorDumper.Parameterizer.OUT_ID
Output file name parameter.
|
static OptionID |
ResultWriter.Parameterizer.OVERWRITE_OPTION_ID
Flag to suppress overwrite warning.
|
static OptionID |
KMLOutputHandler.Parameterizer.SCALING_ID
Parameter for scaling functions
Key:
-kml.scaling
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
EnsembleVotingMedian.Parameterizer.QUANTILE_ID
Option ID for the quantile
|
Modifier and Type | Method and Description |
---|---|
static OptionID |
OptionID.getOrCreateOptionID(String name,
String description)
Gets or creates the OptionID for the given class and given name.
|
Modifier and Type | Field and Description |
---|---|
(package private) LinkedList<Pair<OptionID,Object>> |
ListParameterization.parameters
The actual parameters, for storage
|
private List<Pair<OptionID,Object>> |
MergedParameterization.used
Parameters to rewind.
|
Modifier and Type | Method and Description |
---|---|
List<Pair<OptionID,Object>> |
ListParameterization.getRemainingParameters()
Return the yet unused parameters.
|
Modifier and Type | Method and Description |
---|---|
void |
ListParameterization.addFlag(OptionID optionid)
Add a flag to the parameter list
|
void |
ListParameterization.addParameter(OptionID optionid,
Object value)
Add a parameter to the parameter list
|
Constructor and Description |
---|
ListParameterization(Collection<Pair<OptionID,Object>> dbParameters)
Constructor with an existing collection.
|
MergedParameterization(Parameterization inner,
ListParameterization current,
List<Pair<OptionID,Object>> used)
Constructor for descending
|
Modifier and Type | Field and Description |
---|---|
protected OptionID |
AbstractParameter.optionid
The option name.
|
Modifier and Type | Method and Description |
---|---|
OptionID |
AbstractParameter.getOptionID() |
OptionID |
Parameter.getOptionID()
Return the OptionID of this option.
|
Constructor and Description |
---|
AbstractParameter(OptionID optionID)
Constructs a parameter with the given optionID, and constraints.
|
AbstractParameter(OptionID optionID,
boolean optional)
Constructs a parameter with the given optionID, constraints, and optional
flag.
|
AbstractParameter(OptionID optionID,
T defaultValue)
Constructs a parameter with the given optionID, constraints, and default
value.
|
ClassListParameter(OptionID optionID,
Class<?> restrictionClass)
Constructs a class list parameter with the given optionID and restriction
class.
|
ClassListParameter(OptionID optionID,
Class<?> restrictionClass,
boolean optional)
Constructs a class list parameter with the given optionID and restriction
class.
|
ClassParameter(OptionID optionID,
Class<?> restrictionClass)
Constructs a class parameter with the given optionID, and restriction
class.
|
ClassParameter(OptionID optionID,
Class<?> restrictionClass,
boolean optional)
Constructs a class parameter with the given optionID, restriction class,
and optional flag.
|
ClassParameter(OptionID optionID,
Class<?> restrictionClass,
Class<?> defaultValue)
Constructs a class parameter with the given optionID, restriction class,
and default value.
|
DoubleListParameter(OptionID optionID)
Constructs a list parameter with the given optionID.
|
DoubleListParameter(OptionID optionID,
boolean optional)
Constructs a list parameter with the given optionID and optional flag.
|
DoubleParameter(OptionID optionID)
Constructs a double parameter with the given optionID.
|
DoubleParameter(OptionID optionID,
double defaultValue)
Constructs a double parameter with the given optionID and default value.
|
EnumParameter(OptionID optionID,
Class<E> enumClass)
Constructs an enum parameter with the given optionID, constraints and
default value.
|
EnumParameter(OptionID optionID,
Class<E> enumClass,
boolean optional)
Constructs an enum parameter with the given optionID, constraints and
default value.
|
EnumParameter(OptionID optionID,
Class<E> enumClass,
E defaultValue)
Constructs an enum parameter with the given optionID, constraints and
default value.
|
FileListParameter(OptionID optionID,
FileListParameter.FilesType filesType)
Constructs a file list parameter with the given optionID, and file type.
|
FileParameter(OptionID optionID,
FileParameter.FileType fileType)
Constructs a file parameter with the given optionID, and file type.
|
FileParameter(OptionID optionID,
FileParameter.FileType fileType,
boolean optional)
Constructs a file parameter with the given optionID, file type, and
optional flag.
|
Flag(OptionID optionID)
Constructs a flag object with the given optionID.
|
IntListParameter(OptionID optionID)
Constructs an integer list parameter
|
IntListParameter(OptionID optionID,
boolean optional)
Constructs an integer list parameter
|
IntParameter(OptionID optionID)
Constructs an integer parameter with the given optionID.
|
IntParameter(OptionID optionID,
int defaultValue)
Constructs an integer parameter with the given optionID.
|
ListParameter(OptionID optionID)
Constructs a list parameter with the given optionID.
|
ListParameter(OptionID optionID,
boolean optional)
Constructs a list parameter with the given optionID and optional flag.
|
ListParameter(OptionID optionID,
T defaultValue)
Constructs a list parameter with the given optionID.
|
LongParameter(OptionID optionID)
Constructs a long parameter with the given optionID.
|
LongParameter(OptionID optionID,
long defaultValue)
Constructs a long parameter with the given optionID and default value.
|
NumberParameter(OptionID optionID)
Constructs a number parameter with the given optionID.
|
NumberParameter(OptionID optionID,
boolean optional)
Constructs a number parameter with the given optionID and optional flag.
|
NumberParameter(OptionID optionID,
T defaultValue)
Constructs a number parameter with the given optionID and default Value.
|
ObjectListParameter(OptionID optionID,
Class<?> restrictionClass)
Constructor for non-optional.
|
ObjectListParameter(OptionID optionID,
Class<?> restrictionClass,
boolean optional)
Constructor with optional flag.
|
ObjectParameter(OptionID optionID,
Class<?> restrictionClass)
Constructs a class parameter with the given optionID, and restriction
class.
|
ObjectParameter(OptionID optionID,
Class<?> restrictionClass,
boolean optional)
Constructs a class parameter with the given optionID, restriction class,
and optional flag.
|
ObjectParameter(OptionID optionID,
Class<?> restrictionClass,
Class<?> defaultValue)
Constructs a class parameter with the given optionID, restriction class,
and default value.
|
ObjectParameter(OptionID optionID,
Class<?> restrictionClass,
T defaultValue)
Constructs a class parameter with the given optionID, restriction class,
and default value.
|
PatternParameter(OptionID optionID)
Constructs a pattern parameter with the given optionID.
|
PatternParameter(OptionID optionID,
Pattern defaultValue)
Constructs a pattern parameter with the given optionID, and default value.
|
PatternParameter(OptionID optionID,
String defaultValue)
Constructs a pattern parameter with the given optionID, and default value.
|
RandomParameter(OptionID optionID)
Constructor without default.
|
RandomParameter(OptionID optionID,
long seed)
Constructor with default seed value.
|
RandomParameter(OptionID optionID,
RandomFactory defaultValue)
Constructor with default value.
|
StringParameter(OptionID optionID)
Constructs a string parameter with the given optionID.
|
StringParameter(OptionID optionID,
String defaultValue)
Constructs a string parameter with the given optionID, and default value.
|
VectorListParameter(OptionID optionID)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
boolean optional)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
ParameterConstraint<List<Vector>> constraint)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
ParameterConstraint<List<Vector>> constraint,
boolean optional)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
ParameterConstraint<List<Vector>> constraint,
List<Vector> defaultValue)
Constructs a vector list parameter with the given name and description.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
GridBasedReferencePoints.Parameterizer.GRID_ID
Parameter to specify the grid resolution.
|
static OptionID |
GridBasedReferencePoints.Parameterizer.GRID_SCALE_ID
Parameter to specify the extra scaling of the space, to allow
out-of-data-space reference points.
|
static OptionID |
RandomSampleReferencePoints.Parameterizer.N_ID
Parameter to specify the sample size.
|
static OptionID |
RandomGeneratedReferencePoints.Parameterizer.N_ID
Parameter to specify the number of requested reference points.
|
static OptionID |
StarBasedReferencePoints.Parameterizer.NOCENTER_ID
Parameter to specify the grid resolution.
|
static OptionID |
RandomSampleReferencePoints.Parameterizer.RANDOM_ID
Parameter to specify the sample size.
|
static OptionID |
RandomGeneratedReferencePoints.Parameterizer.RANDOM_ID
Parameter to specify the sample size.
|
static OptionID |
RandomGeneratedReferencePoints.Parameterizer.SCALE_ID
Parameter for additional scaling of the space, to allow out-of-space
reference points.
|
static OptionID |
StarBasedReferencePoints.Parameterizer.SCALE_ID
Parameter to specify the extra scaling of the space, to allow
out-of-data-space reference points.
|
static OptionID |
AxisBasedReferencePoints.Parameterizer.SPACE_SCALE_ID
Parameter to specify the extra scaling of the space, to allow
out-of-data-space reference points.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
GammaScaling.GAMMA_ID
OptionID for the gamma value.
|
static OptionID |
ClipScaling.MAX_ID
Parameter to specify the maximum value
Key:
-clipscale.max
|
static OptionID |
ClipScaling.MIN_ID
Parameter to specify a fixed minimum to use.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
TopKOutlierScaling.BINARY_ID
Parameter to specify the lambda value
Key:
-topk.binary
|
static OptionID |
TopKOutlierScaling.K_ID
Parameter to specify the number of outliers to keep
Key:
-topk.k
|
static OptionID |
SqrtStandardDeviationScaling.Parameterizer.LAMBDA_ID
Parameter to specify the lambda value
Key:
-sqrtstddevscale.lambda
|
static OptionID |
StandardDeviationScaling.Parameterizer.LAMBDA_ID
Parameter to specify the lambda value
Key:
-stddevscale.lambda
|
static OptionID |
OutlierSqrtScaling.Parameterizer.MAX_ID
Parameter to specify the fixed maximum to use.
|
static OptionID |
OutlierLinearScaling.MAX_ID
Parameter to specify the maximum value.
|
static OptionID |
SqrtStandardDeviationScaling.Parameterizer.MEAN_ID
Parameter to specify a fixed mean to use.
|
static OptionID |
StandardDeviationScaling.Parameterizer.MEAN_ID
Parameter to specify a fixed mean to use.
|
static OptionID |
OutlierLinearScaling.MEAN_ID
Flag to use the mean as minimum for scaling.
|
static OptionID |
SqrtStandardDeviationScaling.Parameterizer.MIN_ID
Parameter to specify the fixed minimum to use.
|
static OptionID |
OutlierSqrtScaling.Parameterizer.MIN_ID
Parameter to specify the fixed minimum to use.
|
static OptionID |
OutlierLinearScaling.MIN_ID
Parameter to specify a fixed minimum to use.
|
static OptionID |
OutlierGammaScaling.NORMALIZE_ID
Normalization flag.
|
static OptionID |
OutlierLinearScaling.NOZEROS_ID
Flag to use ignore zeros when computing the min and max.
|
static OptionID |
COPOutlierScaling.Parameterizer.PHI_ID
Phi parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
VisualizerParameterizer.ENABLEVIS_ID
Parameter to enable visualizers
Key: -vis.enable
Default: ELKI core
|
static OptionID |
ExportVisualizations.FOLDER_ID
Parameter to specify the output folder
Key:
-vis.output
|
static OptionID |
ExportVisualizations.RATIO_ID
Parameter to specify the canvas ratio
Key:
-vis.ratio
Default value: 1.33
|
static OptionID |
VisualizerParameterizer.SAMPLING_ID
Parameter to set the sampling level
Key: -vis.sampling
|
static OptionID |
VisualizerParameterizer.STYLELIB_ID
Parameter to get the style properties file.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ResultVisualizer.Parameterizer.SINGLE_ID
Flag to set single display
Key: -vis.single
|
static OptionID |
ResultVisualizer.Parameterizer.WINDOW_TITLE_ID
Parameter to specify the window title
Key:
-vis.window.title
Default value: "ELKI Result Visualization"
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ScatterPlotFactory.Parameterizer.MAXDIM_ID
Parameter for the maximum number of dimensions.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ColoredHistogramVisualizer.Parameterizer.HISTOGRAM_BINS_ID
Parameter to specify the number of bins to use in histogram.
|
static OptionID |
ColoredHistogramVisualizer.Parameterizer.STYLE_CURVES_ID
Flag to specify the "curves" rendering style.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ClusterOutlineVisualization.Parameterizer.STRAIGHT_ID
Option string to draw straight lines for hull.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
TooltipScoreVisualization.Parameterizer.DIGITS_ID
Parameter for the gamma-correction.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ClusterHullVisualization.Parameterizer.ALPHA_ID
Alpha-Value for alpha-shapes
Key:
-hull.alpha
|
static OptionID |
VoronoiVisualization.Parameterizer.MODE_ID
Mode for drawing: Voronoi, Delaunay, both.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
TreeMBRVisualization.Parameterizer.FILL_ID
Flag for half-transparent filling of bubbles.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
BubbleVisualization.Parameterizer.FILL_ID
Flag for half-transparent filling of bubbles.
|
static OptionID |
BubbleVisualization.Parameterizer.SCALING_ID
Parameter for scaling functions
Key:
-bubble.scaling
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
SelectionCubeVisualization.Parameterizer.NOFILL_ID
Flag for half-transparent filling of selection cubes.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AlgorithmStep.Parameterizer.ALGORITHM_ID
Parameter to specify the algorithm to run.
|
static OptionID |
InputStep.Parameterizer.DATABASE_ID
Option ID to specify the database type
Key:
-db
|
static OptionID |
EvaluationStep.Parameterizer.EVALUATOR_ID
Parameter ID to specify the evaluators to run.
|
static OptionID |
OutputStep.Parameterizer.OUTPUT_ID
OptionID for the application output file/folder.
|
static OptionID |
OutputStep.Parameterizer.RESULT_HANDLER_ID
Parameter to specify the result handler classes.
|
static OptionID |
AlgorithmStep.Parameterizer.TIME_ID
Flag to allow verbose messages while running the application.
|
Modifier and Type | Field and Description |
---|---|
private static OptionID |
NaiveAgglomerativeHierarchicalClustering4.Parameterizer.LINKAGE_ID
Option ID for linkage parameter.
|
private static OptionID |
NaiveAgglomerativeHierarchicalClustering3.Parameterizer.LINKAGE_ID
Option ID for linkage parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
MultiLPNorm.Parameterizer.EXPONENTS_ID
Option ID for the exponents
-multinorm.ps
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ODIN.Parameterizer.K_ID
Parameter for the number of nearest neighbors:
-odin.k <int>
|
static OptionID |
DistanceStddevOutlier.Parameterizer.K_ID
Option ID for parameterization.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.