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.
|
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.intrinsic |
Outlier detection algorithms based on intrinsic dimensionality.
|
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.
|
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.
|
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
|
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 |
ValidateApproximativeKNNIndex.Parameterizer.K_ID
Parameter for the number of neighbors.
|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.K_ID
Parameter for the number of neighbors.
|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.PATTERN_ID
Parameter to select query points.
|
static OptionID |
ValidateApproximativeKNNIndex.Parameterizer.QUERY_ID
Parameter for the query dataset.
|
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.RANDOM_ID
Parameter for the random generator.
|
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.SAMPLING_ID
Parameter for the sampling size.
|
static OptionID |
RangeQueryBenchmarkAlgorithm.Parameterizer.SAMPLING_ID
Parameter for the sampling size.
|
static OptionID |
KNNBenchmarkAlgorithm.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 |
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 |
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 |
CASH.JITTER_ID
Parameter to specify the maximum jitter for distance values, must be a
double greater than 0.
|
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 |
ERiC.Settings.Parameterizer.K_ID
Size for the kNN neighborhood used in the PCA step of ERiC.
|
static OptionID |
COPAC.Settings.Parameterizer.K_ID
Size for the kNN neighborhood used in the PCA step of COPAC.
|
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 |
EM.Parameterizer.INIT_ID
Parameter to specify the EM cluster models to use.
|
static OptionID |
AbstractEMModelFactory.Parameterizer.INIT_ID
Parameter to specify the cluster center initialization.
|
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.HIERARCHICAL_ID
Parameter to configure the output mode (nested or truncated clusters).
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.MINCLUSTERS_ID
The minimum number of clusters to extract.
|
static OptionID |
SimplifiedHierarchyExtraction.Parameterizer.MINCLUSTERSIZE_ID
The minimum size of clusters to extract.
|
static OptionID |
HDBSCANHierarchyExtraction.Parameterizer.MINCLUSTERSIZE_ID
The minimum size of clusters to extract.
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.MODE_ID
Extraction mode to use.
|
static OptionID |
ExtractFlatClusteringFromHierarchy.Parameterizer.NO_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 |
XMeans.Parameterizer.SEED_ID
Randomization seed.
|
static OptionID |
KMeans.SEED_ID
Parameter to specify the random generator 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 |
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 |
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 |
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 |
ByModelClustering.NOISE_ID
Pattern to recognize noise clusters with
|
static OptionID |
ByLabelClustering.NOISE_ID
Pattern to recognize noise clusters by.
|
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 |
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 |
DWOF.Parameterizer.K_ID
Option ID for the number of neighbors.
|
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 |
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 |
SimpleCOP.Parameterizer.PCARUNNER_ID
Parameter for the PCA runner class.
|
static OptionID |
COP.Parameterizer.PCARUNNER_ID
Class to compute the PCA with.
|
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 |
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 |
ODIN.Parameterizer.K_ID
Parameter for the number of nearest neighbors:
-odin.k <int>
|
static OptionID |
LocalIsolationCoefficient.Parameterizer.K_ID
Parameter to specify the k nearest neighbor.
|
static OptionID |
KNNWeightOutlier.Parameterizer.K_ID
Parameter to specify the k nearest neighbor.
|
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 |
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 |
IntrinsicDimensionalityOutlier.Parameterizer.ESTIMATOR_ID
Class to use for estimating the ID.
|
static OptionID |
IDOS.Parameterizer.ESTIMATOR_ID
The class used for estimating the intrinsic dimensionality.
|
static OptionID |
IntrinsicDimensionalityOutlier.Parameterizer.K_ID
Parameter for the number of neighbors.
|
static OptionID |
IDOS.Parameterizer.KC_ID
Parameter to specify the number of nearest neighbors of an object to be
used for the GED computation.
|
static OptionID |
IDOS.Parameterizer.KR_ID
Parameter to specify the neighborhood size to use for the averaging.
|
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 |
VarianceOfVolume.Parameterizer.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its VOV score, must be an integer greater than
or equal to 1.
|
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.Parameterizer.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 |
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 |
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 |
SimpleKernelDensityLOF.Parameterizer.KERNEL_ID
Option ID for kernel density LOF kernel.
|
static OptionID |
LDF.Parameterizer.KERNEL_ID
Option ID for kernel.
|
private static OptionID |
KDEOS.Parameterizer.KERNEL_ID
Parameter to specify the kernel density function.
|
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 |
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.KREACH_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its reachability distance.
|
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 |
LoOP.Parameterizer.REACHABILITY_DISTANCE_FUNCTION_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
FlexibleLOF.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 |
RescaleMetaOutlierAlgorithm.SCALING_ID
Parameter to specify a scaling function to use.
|
static OptionID |
ExternalDoubleOutlierScore.Parameterizer.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 |
CTLuRandomWalkEC.Parameterizer.ALPHA_ID
Parameter to specify alpha.
|
static OptionID |
CTLuGLSBackwardSearchAlgorithm.Parameterizer.ALPHA_ID
Holds the alpha value - significance niveau
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.C_ID
Parameter to specify the c.
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.K_ID
Parameter to specify the number of neighbors.
|
static OptionID |
CTLuGLSBackwardSearchAlgorithm.Parameterizer.K_ID
Parameter to specify the k nearest 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 |
---|---|
static OptionID |
EstimateIntrinsicDimensionality.Parameterizer.ESTIMATOR_ID
Estimation method
|
static OptionID |
DistanceStatisticsWithClasses.Parameterizer.EXACT_ID
Flag to compute exact value range for binning.
|
static OptionID |
RankingQualityHistogram.Parameterizer.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
EvaluateRankingQuality.Parameterizer.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
DistanceStatisticsWithClasses.Parameterizer.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
EvaluateRetrievalPerformance.Parameterizer.INCLUDESELF_ID
Parameter to include the query object.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.INCLUDESELF_ID
Parameter to include the query object.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.K_ID
Parameter for k.
|
private static OptionID |
AveragePrecisionAtK.Parameterizer.K_ID
Parameter k to compute the average precision at.
|
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 |
DistanceQuantileSampler.Parameterizer.NOZEROS_ID
Flag to ignore zero distances (recommended with many duplicates).
|
static OptionID |
DistanceQuantileSampler.Parameterizer.QUANTILE_ID
Quantile to compute.
|
static OptionID |
RangeQuerySelectivity.Parameterizer.RADIUS_ID
Parameter to specify the query radius.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.REP_ID
Parameter to specify the number of repetitions of computing the hopkins
value.
|
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 |
RangeQuerySelectivity.Parameterizer.SAMPLING_ID
Parameter to enable sampling.
|
static OptionID |
EvaluateRetrievalPerformance.Parameterizer.SAMPLING_ID
Parameter to enable sampling.
|
static OptionID |
DistanceStatisticsWithClasses.Parameterizer.SAMPLING_ID
Flag to enable sampling.
|
static OptionID |
DistanceQuantileSampler.Parameterizer.SAMPLING_ID
Sampling rate.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.SAMPLING_ID
Parameter to enable sampling.
|
static OptionID |
RangeQuerySelectivity.Parameterizer.SEED_ID
Parameter to control the sampling random seed.
|
static OptionID |
HopkinsStatisticClusteringTendency.Parameterizer.SEED_ID
Parameter to specify the random generator seed.
|
static OptionID |
EvaluateRetrievalPerformance.Parameterizer.SEED_ID
Parameter to control the sampling random seed.
|
static OptionID |
DistanceQuantileSampler.Parameterizer.SEED_ID
Random generator seed.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.SEED_ID
Parameter to control the sampling random 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 |
CacheDoubleDistanceRangeQueries.Parameterizer.CACHE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceKNNLists.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 |
CacheDoubleDistanceRangeQueries.Parameterizer.DISTANCE_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 |
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.DISABLE_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 |
UniformUncertainifier.Parameterizer.DEV_MAX_ID
Maximum deviation of the generated bounding box.
|
static OptionID |
SimpleGaussianUncertainifier.Parameterizer.DEV_MAX_ID
Parameter for maximum 3-sigma deviation.
|
static OptionID |
UniformUncertainifier.Parameterizer.DEV_MIN_ID
Minimum deviation of the generated bounding box.
|
static OptionID |
SimpleGaussianUncertainifier.Parameterizer.DEV_MIN_ID
Parameter for minimum 3-sigma deviation.
|
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.Parameterizer.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.Parameterizer.RANDOMSEED_ID
Parameter to give the configuration file
|
static OptionID |
GeneratorXMLDatabaseConnection.Parameterizer.REASSIGN_ID
Parameter for cluster reassignment
|
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.Parameterizer.SIZE_SCALE_ID
Parameter to give the configuration file
|
static OptionID |
PresortedBlindJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
static OptionID |
LabelJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
static OptionID |
ExternalIDJoinDatabaseConnection.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 |
PerturbationFilter.Parameterizer.SEED_ID
Optional parameter to specify a seed for random Gaussian noise
generation.
|
static OptionID |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.SEED_ID
Optional parameter to specify a seed for random projection.
|
static OptionID |
HistogramJitterFilter.Parameterizer.SEED_ID
Option ID for the jitter random seed.
|
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 |
WeightedUncertainSplitFilter.Parameterizer.DIM_ID
Parameter for specifying the number of dimensions of the sample.
|
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 |
WeightedUncertainSplitFilter.Parameterizer.PROBCOL_ID
Parameter to specify where the probability is stored.
|
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 |
RGBHistogramQuadraticDistanceFunction.BPP_ID
Parameter for the kernel dimensionality.
|
static OptionID |
HSBHistogramQuadraticDistanceFunction.BPP_ID
Parameter for the kernel dimensionality.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
FileBasedDoubleDistanceFunction.Parameterizer.MATRIX_ID
Parameter that specifies the name of the distance matrix file.
|
static OptionID |
DiskCacheBasedDoubleDistanceFunction.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 |
RadialBasisFunctionKernelFunction.Parameterizer.SIGMA_ID
Sigma parameter: standard deviation.
|
static OptionID |
LaplaceKernelFunction.Parameterizer.SIGMA_ID
Sigma parameter: standard deviation.
|
static OptionID |
SigmoidKernelFunction.Parameterizer.THETA_ID
Theta parameter: bias
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
StratifiedCrossValidation.Parameterizer.NFOLD_ID
Parameter for number of folds.
|
static OptionID |
RandomizedCrossValidation.Parameterizer.NFOLD_ID
Parameter for number of folds.
|
static OptionID |
DisjointCrossValidation.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 |
EvaluateSquaredErrors.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateSilhouette.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluatePBMIndex.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateDaviesBouldin.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateConcordantPairs.Parameterizer.DISTANCE_ID
Parameter for choosing the distance function.
|
static OptionID |
EvaluateCIndex.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 |
EvaluateSquaredErrors.Parameterizer.NOISE_ID
Parameter to treat noise as a single cluster.
|
static OptionID |
EvaluateSilhouette.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 |
EvaluateDaviesBouldin.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 |
EvaluateCIndex.Parameterizer.NOISE_ID
Parameter for the option, how noise should be treated.
|
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 |
OutlierRankingEvaluation.Parameterizer.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
OutlierROCCurve.Parameterizer.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
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 |
JudgeOutlierScores.POSITIVE_CLASS_NAME_ID
The distance function to determine the reachability distance between
database objects.
|
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 |
RandomProjectedNeighborsAndDensities.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 |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.CURVES_ID
Parameter for choosing the space filling curves to use.
|
static OptionID |
SpacefillingKNNPreprocessor.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 |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.RANDOM_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
SpacefillingKNNPreprocessor.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 |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
SpacefillingKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID
Parameter for choosing the number of variants to use.
|
static OptionID |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.WINDOW_ID
Parameter for setting the widows size multiplicator.
|
static OptionID |
SpacefillingKNNPreprocessor.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 |
VAFile.Factory.PARTITIONS_ID
Number of partitions to use in each dimension.
|
static OptionID |
PartialVAFile.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 |
LaplaceDistribution.Parameterizer.RATE_ID
Shape parameter gamma.
|
static OptionID |
ExponentialDistribution.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 |
LogNormalDistribution.Parameterizer.SHIFT_ID
Shift parameter
|
static OptionID |
LogGammaDistribution.Parameterizer.SHIFT_ID
Shifting offset parameter.
|
static OptionID |
LogGammaAlternateDistribution.Parameterizer.SHIFT_ID
Shifting offset 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 |
WinsorisingEstimator.Parameterizer.INNER_ID
Option for the class to use on the winsorized sample.
|
static OptionID |
TrimmedEstimator.Parameterizer.INNER_ID
Option for the class to use on the trimmed 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 |
Parameter.getOptionID()
Return the OptionID of this option.
|
OptionID |
AbstractParameter.getOptionID() |
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 |
StarBasedReferencePoints.Parameterizer.SCALE_ID
Parameter to specify the extra scaling of the space, to allow
out-of-data-space reference points.
|
static OptionID |
RandomGeneratedReferencePoints.Parameterizer.SCALE_ID
Parameter for additional scaling of the space, to allow out-of-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 |
StandardDeviationScaling.Parameterizer.LAMBDA_ID
Parameter to specify the lambda value
Key:
-stddevscale.lambda
|
static OptionID |
SqrtStandardDeviationScaling.Parameterizer.LAMBDA_ID
Parameter to specify the lambda value
Key:
-sqrtstddevscale.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 |
StandardDeviationScaling.Parameterizer.MEAN_ID
Parameter to specify a fixed mean to use.
|
static OptionID |
SqrtStandardDeviationScaling.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.Parameterizer.ENABLEVIS_ID
Parameter to enable visualizers
Key: -vis.enable
Default: ELKI core
|
static OptionID |
ExportVisualizations.Parameterizer.FOLDER_ID
Parameter to specify the output folder
Key:
-vis.output
|
static OptionID |
ExportVisualizations.Parameterizer.RATIO_ID
Parameter to specify the canvas ratio
Key:
-vis.ratio
Default value: 1.33
|
static OptionID |
VisualizerParameterizer.Parameterizer.SAMPLING_ID
Parameter to set the sampling level
Key: -vis.sampling
|
static OptionID |
VisualizerParameterizer.Parameterizer.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.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.