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.clustering |
Clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected clustering algorithms or
subspace clustering algorithms according to the classical but somewhat obsolete classification schema
of clustering algorithms for axis-parallel subspaces.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.trivial |
Trivial clustering algorithms: all in one, no clusters, label clusterings
These methods are mostly useful for providing a reference result in evaluation.
|
de.lmu.ifi.dbs.elki.algorithm.outlier |
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.trivial |
Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms
The algorithms in this package perform statistical analysis of the data
(e.g. compute distributions, distance distributions etc.)
|
de.lmu.ifi.dbs.elki.application |
Base classes for stand alone applications.
|
de.lmu.ifi.dbs.elki.application.cache |
Utility applications for the persistence layer such as distance cache builders.
|
de.lmu.ifi.dbs.elki.application.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.application.visualization |
Visualization applications in ELKI.
|
de.lmu.ifi.dbs.elki.data.images |
Package for processing image data (e.g. compute color histograms)
|
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.normalization |
Data normalization.
|
de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations.
|
de.lmu.ifi.dbs.elki.datasource.parser |
Parsers for different file formats and data types.
|
de.lmu.ifi.dbs.elki.distance.distancefunction |
Distance functions for use within ELKI.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.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.correlation |
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.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.clustering |
Evaluation of clustering results.
|
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.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.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.preprocessed.subspaceproj |
Index using a preprocessed local subspaces.
|
de.lmu.ifi.dbs.elki.index.tree |
Tree-based index structures
|
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.spatial.rstarvariants |
R*-Tree and variants.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk |
Packages for bulk-loading R*-Trees.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert |
Insertion strategies for R-Trees
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.overflow |
Overflow treatment strategies for R-Trees
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert |
Reinsertion strategies for R-Trees
|
de.lmu.ifi.dbs.elki.index.vafile |
Vector Approximation File
|
de.lmu.ifi.dbs.elki.math.linearalgebra.pca |
Principal Component Analysis (PCA) and Eigenvector processing.
|
de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
de.lmu.ifi.dbs.elki.utilities.ensemble |
Utility classes for simple ensembles.
|
de.lmu.ifi.dbs.elki.utilities.optionhandling |
Parameter handling and option descriptions.
|
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization |
Configuration managers
See the
de.lmu.ifi.dbs.elki.utilities.optionhandling package for documentation! |
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters |
Classes for various typed parameters.
|
de.lmu.ifi.dbs.elki.utilities.referencepoints |
Package containing strategies to obtain reference points
Shared code for various algorithms that use reference points.
|
de.lmu.ifi.dbs.elki.utilities.scaling |
Scaling functions: linear, logarithmic, gamma, clipping, ...
|
de.lmu.ifi.dbs.elki.utilities.scaling.outlier |
Scaling of Outlier scores, that require a statistical analysis of the occurring values
|
de.lmu.ifi.dbs.elki.visualization |
Visualization package of ELKI.
|
de.lmu.ifi.dbs.elki.visualization.gui |
Package to provide a visualization GUI.
|
de.lmu.ifi.dbs.elki.visualization.projector |
Projectors are responsible for finding appropriate projections for data relations.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.histogram |
Visualizers based on 1D projected histograms.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster |
Visualizers for clustering results based on parallel coordinates.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot |
Visualizers based on scatterplots.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster |
Visualizers for clustering results based on 2D projections.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index |
Visualizers for index structures based on 2D projections.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier |
Visualizers for outlier scores based on 2D projections.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection |
Visualizers for object selection based on 2D projections.
|
tutorial.distancefunction |
Classes from the tutorial on implementing distance functions.
|
tutorial.outlier |
Modifier and Type | Field and Description |
---|---|
static OptionID |
DependencyDerivator.DEPENDENCY_DERIVATOR_RANDOM_SAMPLE
Flag to use random sample (use knn query around centroid, if flag is not
set).
|
static OptionID |
AbstractDistanceBasedAlgorithm.DISTANCE_FUNCTION_ID
OptionID for
AbstractDistanceBasedAlgorithm.DISTANCE_FUNCTION_ID . |
static OptionID |
KNNJoin.K_ID
Parameter that specifies the k-nearest neighbors to be assigned, must be an
integer greater than 0.
|
static OptionID |
KNNDistanceOrder.K_ID
Parameter to specify the distance of the k-distant object to be assessed,
must be an integer greater than 0.
|
static OptionID |
APRIORI.MINFREQ_ID
Optional parameter to specify the threshold for minimum frequency, must be
a double greater than or equal to 0 and less than or equal to 1.
|
static OptionID |
APRIORI.MINSUPP_ID
Parameter to specify the threshold for minimum support as minimally
required number of transactions, must be an integer equal to or 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 |
KNNDistanceOrder.PERCENTAGE_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 |
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.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.K_ID
Parameter for the number of neighbors.
|
static OptionID |
RangeQueryBenchmarkAlgorithm.Parameterizer.QUERY_ID
Parameter for the query dataset.
|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.QUERY_ID
Parameter for the query dataset.
|
static OptionID |
RangeQueryBenchmarkAlgorithm.Parameterizer.RANDOM_ID
Parameter for the random generator
|
static OptionID |
KNNBenchmarkAlgorithm.Parameterizer.RANDOM_ID
Parameter for the random generator
|
static OptionID |
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 |
EM.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 |
OPTICS.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to the distance function specified.
|
static OptionID |
SNNClustering.EPSILON_ID
Parameter to specify the minimum SNN density, must be an integer greater
than 0.
|
static OptionID |
DBSCAN.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to the distance function specified.
|
static OptionID |
AbstractProjectedDBSCAN.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to
LocallyWeightedDistanceFunction . |
static OptionID |
EM.INIT_ID
Parameter to specify the initialization method
|
static OptionID |
AbstractProjectedDBSCAN.INNER_DISTANCE_FUNCTION_ID
Parameter distance function
|
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 |
EM.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 |
AbstractProjectedDBSCAN.LAMBDA_ID
Parameter to specify the intrinsic dimensionality of the clusters to find,
must be an integer greater than 0.
|
static OptionID |
OPTICS.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 |
SNNClustering.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 |
DeLiClu.MINPTS_ID
Parameter to specify the threshold for minimum number of points within a
cluster, must be an integer greater than 0.
|
static OptionID |
DBSCAN.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 |
AbstractProjectedDBSCAN.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 |
AbstractProjectedDBSCAN.OUTER_DISTANCE_FUNCTION_ID
Parameter to specify the distance function to determine the distance
between database objects, must extend
LocallyWeightedDistanceFunction
. |
static OptionID |
NaiveMeanShiftClustering.Parameterizer.RANGE_ID
Parameter for kernel radius/range/bandwidth.
|
static OptionID |
SLINK.Parameterizer.SLINK_MINCLUSTERS_ID
The minimum number of clusters to extract
|
static OptionID |
OPTICSXi.XI_ID
Parameter to specify the steepness threshold.
|
static OptionID |
OPTICSXi.XIALG_ID
Parameter to specify the actual OPTICS algorithm to use.
|
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 |
HiCO.ALPHA_ID
The threshold for 'strong' eigenvectors: the 'strong' eigenvectors explain
a portion of at least alpha of the total variance.
|
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.DELTA_ID
Parameter to specify the threshold of a distance between a vector q and a
given space that indicates that q adds a new dimension to the space, must
be a double equal to or greater than 0.
|
static OptionID |
CASH.JITTER_ID
Parameter to specify the maximum jitter for distance values, must be a
double greater than 0.
|
static OptionID |
HiCO.K_ID
Optional parameter to specify the number of nearest neighbors considered in
the PCA, must be an integer greater than 0.
|
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.MU_ID
Parameter to specify the smoothing factor, must be an integer greater than
0.
|
static OptionID |
COPAC.PARTITION_ALGORITHM_ID
Parameter to specify the clustering algorithm to apply to each partition,
must extend
ClusteringAlgorithm . |
static OptionID |
COPAC.PARTITION_DISTANCE_ID
Parameter to specify the distance function to use inside the partitions
AbstractIndexBasedDistanceFunction
. |
static OptionID |
COPAC.PREPROCESSOR_ID
Parameter to specify the local PCA preprocessor to derive partition
criterion, must extend
AbstractFilteredPCAIndex . |
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 |
LMCLUS.Parameterizer.THRESHOLD_ID
Global significance threshold
|
Modifier and Type | Field and Description |
---|---|
protected Collection<Pair<OptionID,Object>> |
COPAC.Parameterizer.algO |
private Collection<Pair<OptionID,Object>> |
COPAC.partitionAlgorithmParameters
Holds the parameters of the algorithm to run on each partition.
|
Constructor and Description |
---|
COPAC(FilteredLocalPCABasedDistanceFunction<V,?,D> partitionDistanceFunction,
Class<? extends ClusteringAlgorithm<Clustering<Model>>> partitionAlgorithm,
Collection<Pair<OptionID,Object>> partitionAlgorithmParameters)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
GeneralizedDBSCAN.Parameterizer.COREPRED_ID
Parameter for core predicate
|
static OptionID |
GeneralizedDBSCAN.Parameterizer.NEIGHBORHOODPRED_ID
Parameter for neighborhood predicate
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
KMeans.INIT_ID
Parameter to specify the initialization method
|
static OptionID |
KMeans.K_ID
Parameter to specify the number of clusters to find, must be an integer
greater than 0.
|
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 |
KMeans.SEED_ID
Parameter to specify the random generator seed.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
SUBCLU.DISTANCE_FUNCTION_ID
The distance function to determine the distance between database objects.
|
static OptionID |
DiSH.EPSILON_ID
Parameter that specifies the maximum radius of the neighborhood to be
considered in each dimension for determination of the preference vector,
must be a double equal to or greater than 0.
|
static OptionID |
SUBCLU.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered, must be suitable to
AbstractDimensionsSelectingDoubleDistanceFunction . |
static OptionID |
PROCLUS.M_I_ID
Parameter to specify the multiplier for the initial number of medoids, must
be an integer greater than 0.
|
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.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 |
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 |
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 |
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 |
---|---|
private Collection<Pair<OptionID,Object>> |
DiSH.opticsAlgorithmParameters
Parameters that were given to OPTICS
|
protected Collection<Pair<OptionID,Object>> |
DiSH.Parameterizer.opticsO |
Constructor and Description |
---|
DiSH(double epsilon,
DiSHDistanceFunction dishDistance,
Collection<Pair<OptionID,Object>> opticsAlgorithmParameters)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ByLabelClustering.MULTIPLE_ID
Flag to indicate that multiple cluster assignment is possible.
|
static OptionID |
ByLabelClustering.NOISE_ID
Pattern to recognize noise clusters by.
|
static OptionID |
ByModelClustering.NOISE_ID
Pattern to recognize noise clusters with
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
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 |
GaussianUniformMixture.C_ID
Parameter to specify the cutoff.
|
static OptionID |
LDF.Parameterizer.C_ID
Option ID for c
|
static OptionID |
LoOP.COMPARISON_DISTANCE_FUNCTION_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
AbstractDBOutlier.D_ID
Parameter to specify the size of the D-neighborhood
|
static OptionID |
COP.Parameterizer.DIST_ID
Distribution assumption for distances.
|
static OptionID |
COP.Parameterizer.EXPECT_ID
Expected share of outliers.
|
static OptionID |
ABOD.FAST_SAMPLE_ID
Parameter for sample size to be used in fast mode.
|
static OptionID |
ALOCI.Parameterizer.GRIDS_ID
Parameter to specify the number of Grids to use.
|
static OptionID |
HilOut.Parameterizer.H_ID
Parameter to specify the maximum Hilbert-Level
|
static OptionID |
LDF.Parameterizer.H_ID
Option ID for h - kernel bandwidth scaling
|
static OptionID |
GaussianModel.INVERT_ID
OptionID for inversion flag.
|
static OptionID |
INFLO.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its INFLO_SCORE. must be an integer greater than
1.
|
static OptionID |
KNNOutlier.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 |
LDF.Parameterizer.K_ID
Option ID for k
|
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 |
ReferenceBasedOutlierDetection.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 |
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 |
AbstractAggarwalYuOutlier.Parameterizer.K_ID
OptionID for the target dimensionality.
|
static OptionID |
ABOD.K_ID
Parameter for k, the number of neighbors used in kNN queries.
|
static OptionID |
LDOF.K_ID
Parameter to specify the number of nearest neighbors of an object to be
considered for computing its LDOF_SCORE, must be an integer greater than 1.
|
static OptionID |
KNNWeightOutlier.K_ID
Parameter to specify the k nearest neighbor
|
static OptionID |
LOF.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 1.
|
static OptionID |
LoOP.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 |
ABOD.KERNEL_FUNCTION_ID
Parameter for the kernel function.
|
static OptionID |
SimpleKernelDensityLOF.Parameterizer.KERNEL_ID
Option ID for kernel density LOF kernel.
|
static OptionID |
LDF.Parameterizer.KERNEL_ID
Option ID for kernel.
|
static OptionID |
KNNWeightOutlier.KNNQUERY_ID
The kNN query used.
|
static OptionID |
LoOP.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 |
GaussianUniformMixture.L_ID
Parameter to specify the fraction of expected outliers.
|
static OptionID |
LoOP.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.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 |
AggarwalYuEvolutionary.Parameterizer.M_ID
Parameter to specify the number of solutions must be an integer greater
than 1.
|
static OptionID |
HilOut.Parameterizer.N_ID
Parameter to specify how many outliers should be computed
|
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 |
DBOutlierDetection.P_ID
Parameter to specify the minimum fraction of objects that must be outside
the D- neighborhood of an outlier
|
static OptionID |
SimpleCOP.Parameterizer.PCARUNNER_ID
Parameter for the PCA runner class.
|
static OptionID |
COP.Parameterizer.PCARUNNER_ID
Class to compute the PCA with.
|
static OptionID |
AbstractAggarwalYuOutlier.Parameterizer.PHI_ID
OptionID for the grid size.
|
static OptionID |
ABOD.PREPROCESSOR_ID
The preprocessor used to materialize the kNN neighborhoods.
|
static OptionID |
LoOP.REACHABILITY_DISTANCE_FUNCTION_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
LOF.REACHABILITY_DISTANCE_FUNCTION_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
ReferenceBasedOutlierDetection.REFP_ID
Parameter for the reference points heuristic.
|
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 |
AggarwalYuEvolutionary.Parameterizer.SEED_ID
Parameter to specify the random generator seed.
|
static OptionID |
ALOCI.Parameterizer.SEED_ID
Parameter to specify the seed to initialize Random.
|
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 |
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 |
FeatureBagging.Parameterizer.SEED_ID
The parameter to specify the random seed.
|
static OptionID |
HiCS.Parameterizer.SEED_ID
Parameter that specifies the random seed.
|
static OptionID |
HiCS.Parameterizer.TEST_ID
Parameter that specifies which statistical test to use in order to
calculate the deviation of two given data samples.
|
static OptionID |
SimpleOutlierEnsemble.Parameterizer.VOTING_ID
Voting strategy to use in the ensemble.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CTLuGLSBackwardSearchAlgorithm.Parameterizer.ALPHA_ID
Holds the alpha value - significance niveau
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.ALPHA_ID
Parameter to specify alpha.
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.C_ID
Parameter to specify the c.
|
static OptionID |
CTLuGLSBackwardSearchAlgorithm.Parameterizer.K_ID
Parameter to specify the k nearest neighbors
|
static OptionID |
CTLuRandomWalkEC.Parameterizer.K_ID
Parameter to specify the number of neighbors.
|
static OptionID |
AbstractNeighborhoodOutlier.NEIGHBORHOOD_ID
Parameter to specify the neighborhood predicate to use.
|
static OptionID |
AbstractDistanceBasedSpatialOutlier.NON_SPATIAL_DISTANCE_FUNCTION_ID
Parameter to specify the non spatial distance function to use
|
static OptionID |
TrimmedMeanApproach.Parameterizer.P_ID
Parameter for the percentile value p.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer.DISTANCEFUNCTION_ID
Parameter to specify the distance function to use
|
static OptionID |
PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer.K_ID
Parameter k
|
static OptionID |
ExternalNeighborhood.NEIGHBORHOOD_FILE_ID
Parameter to specify the neighborhood file
|
static OptionID |
ExtendedNeighborhood.Factory.Parameterizer.NEIGHBORHOOD_ID
Parameter to specify the neighborhood predicate to use.
|
static OptionID |
ExtendedNeighborhood.Factory.Parameterizer.STEPS_ID
Parameter to specify the number of steps allowed
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
UnweightedNeighborhoodAdapter.Factory.Parameterizer.INNER_ID
The parameter to give the non-weighted neighborhood to use.
|
static OptionID |
LinearWeightedExtendedNeighborhood.Factory.Parameterizer.NEIGHBORHOOD_ID
Parameter to specify the neighborhood predicate to use.
|
static OptionID |
LinearWeightedExtendedNeighborhood.Factory.Parameterizer.STEPS_ID
Parameter to specify the number of steps allowed
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
OutRankS1.Parameterizer.ALGORITHM_ID
Clustering algorithm to use.
|
static OptionID |
OutRankS1.Parameterizer.ALPHA_ID
Alpha parameter for S1
|
static OptionID |
SOD.ALPHA_ID
Parameter to indicate the multiplier for the discriminance value for
discerning small from large variances.
|
static OptionID |
OUTRES.Parameterizer.D_ID
Option ID for Epsilon parameter
|
static OptionID |
SOD.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 |
SOD.SIM_ID
Parameter for the similarity function.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
TrivialGeneratedOutlier.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 |
DistanceStatisticsWithClasses.EXACT_ID
Flag to compute exact value range for binning.
|
static OptionID |
RankingQualityHistogram.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
DistanceStatisticsWithClasses.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
static OptionID |
EvaluateRankingQuality.HISTOGRAM_BINS_ID
Option to configure the number of bins to use.
|
private static OptionID |
AveragePrecisionAtK.Parameterizer.K_ID
Parameter k to compute the average precision at.
|
static OptionID |
AddSingleScale.Parameterizer.MINMAX_ID
Minimum and maximum values.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.SAMPLING_ID
Parameter to enable sampling.
|
static OptionID |
DistanceStatisticsWithClasses.SAMPLING_ID
Flag to enable sampling.
|
static OptionID |
AveragePrecisionAtK.Parameterizer.SEED_ID
Parameter to control the sampling random seed.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ComputeSingleColorHistogram.COLORHIST_ID
Class parameter for computing the color histogram.
|
static OptionID |
AbstractApplication.Parameterizer.INPUT_ID
Parameter that specifies the name of the input file.
|
static OptionID |
ComputeSingleColorHistogram.INPUT_ID
Parameter that specifies the name of the input file.
|
static OptionID |
ComputeSingleColorHistogram.MASK_ID
Parameter that specifies the name of the mask input file.
|
static OptionID |
AbstractApplication.Parameterizer.OUTPUT_ID
Parameter that specifies the name of the output file.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
CacheFloatDistanceInOnDiskMatrix.CACHE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceInOnDiskMatrix.CACHE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheFloatDistanceInOnDiskMatrix.DISTANCE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
static OptionID |
CacheDoubleDistanceInOnDiskMatrix.DISTANCE_ID
Parameter that specifies the name of the directory to be re-parsed.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
VisualizeGeodesicDistances.Parameterizer.MODE_ID
Visualization mode.
|
static OptionID |
VisualizeGeodesicDistances.Parameterizer.STEPS_ID
Number of steps in the distance map.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.MAXK_ID
Option ID for k step size.
|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.STARTK_ID
Option ID for k start size.
|
static OptionID |
ComputeKNNOutlierScores.Parameterizer.STEPK_ID
Option ID for k step size.
|
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(HashMapList<Class<?>,Parameter<?>> byclass,
HashMapList<OptionID,Pair<Parameter<?>,Class<?>>> byopt) |
private static Document |
DocumentParameters.makeByOptOverview(HashMapList<OptionID,Pair<Parameter<?>,Class<?>>> byopt) |
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 |
KNNExplorer.DISTANCE_FUNCTION_ID
Parameter to specify the distance function to determine the distance
between database objects, must extend
DistanceFunction . |
Modifier and Type | Field and Description |
---|---|
static OptionID |
ComputeNaiveHSBColorHistogram.BINSPERPLANE_ID
Parameter that specifies the number of bins (per plane) to use.
|
static OptionID |
ComputeNaiveRGBColorHistogram.BINSPERPLANE_ID
Parameter that specifies the number of bins (per plane) to use.
|
static OptionID |
ComputeHSBColorHistogram.BINSPERPLANE_ID
Parameter that specifies the number of bins (per plane) to use.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractDatabase.INDEX_ID
Parameter to specify the indexes to use.
|
Modifier and Type | Field and Description |
---|---|
private static OptionID |
BundleDatabaseConnection.Parameterizer.BUNDLE_ID
Option ID for the bundle parameter.
|
static OptionID |
GeneratorXMLDatabaseConnection.CONFIGFILE_ID
Parameter to give the configuration file
|
private 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.FILTERS_ID
Filters to apply to the input data.
|
static OptionID |
FileBasedDatabaseConnection.INPUT_ID
Parameter that specifies the name of the input file to be parsed.
|
static OptionID |
AbstractDatabaseConnection.PARSER_ID
Parameter to specify the parser to provide a database.
|
static OptionID |
GeneratorXMLDatabaseConnection.RANDOMSEED_ID
Parameter to give the configuration file
|
static OptionID |
RandomDoubleVectorDatabaseConnection.Parameterizer.SEED_ID
Random generator seed.
|
static OptionID |
RandomDoubleVectorDatabaseConnection.Parameterizer.SIZE_ID
Parameter to specify the database size to generate.
|
static OptionID |
GeneratorXMLDatabaseConnection.SIZE_SCALE_ID
Parameter to give the configuration file
|
static OptionID |
ExternalIDJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
static OptionID |
LabelJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
static OptionID |
PresortedBlindJoinDatabaseConnection.Parameterizer.SOURCES_ID
The static option ID
|
private static OptionID |
DBIDRangeDatabaseConnection.Parameterizer.START_ID
Parameter for starting ID to generate
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ClassLabelFilter.CLASS_LABEL_CLASS_ID
Parameter to specify the class of occurring class labels.
|
static OptionID |
ClassLabelFilter.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 |
ExternalIDFilter.EXTERNALID_INDEX_ID
Parameter that specifies the index of the label to be used as external Id,
must be an integer equal to or greater than 0.
|
static OptionID |
FixedDBIDsFilter.IDSTART_ID
Optional parameter to specify the first object ID to use.
|
static OptionID |
HistogramJitterFilter.Parameterizer.JITTER_ID
Option ID for the jitter strength.
|
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.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
|
static OptionID |
HistogramJitterFilter.Parameterizer.SEED_ID
Option ID for the jitter random seed.
|
static OptionID |
SplitNumberVectorFilter.Parameterizer.SELECTED_ATTRIBUTES_ID
The parameter listing the split dimensions.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AttributeWiseMinMaxNormalization.MAXIMA_ID
Parameter for maximum.
|
static OptionID |
AttributeWiseVarianceNormalization.MEAN_ID
Parameter for means.
|
static OptionID |
AttributeWiseMinMaxNormalization.MINIMA_ID
Parameter for minimum.
|
static OptionID |
LengthNormalization.Parameterizer.NORM_ID
Option ID for normalization norm.
|
static OptionID |
AttributeWiseVarianceNormalization.STDDEV_ID
Parameter for stddevs.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
GlobalPrincipalComponentAnalysisTransform.Parameterizer.FILTER_ID
To specify the eigenvectors to keep.
|
static OptionID |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.NUMBER_SELECTED_ATTRIBUTES_ID
Parameter for the desired cardinality of the subset of attributes
selected for projection.
|
static OptionID |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.SEED_ID
Optional parameter to specify a seed for random projection.
|
static OptionID |
NumberVectorFeatureSelectionFilter.Parameterizer.SELECTED_ATTRIBUTES_ID
Selected attributes parameter.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractParser.COLUMN_SEPARATOR_ID
OptionID for the column separator parameter (defaults to whitespace as in
AbstractParser.DEFAULT_SEPARATOR . |
static OptionID |
NumberVectorLabelParser.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 |
AbstractParser.QUOTE_ID
OptionID for the quote character parameter (defaults to a double quotation
mark as in
AbstractParser.QUOTE_CHAR . |
static OptionID |
NumberVectorLabelParser.VECTOR_TYPE_ID
Parameter to specify the type of vectors to produce.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
MinKDistance.DISTANCE_FUNCTION_ID
OptionID for the base distance used to compute reachability
|
static OptionID |
IndexBasedDistanceFunction.INDEX_ID
OptionID for the index parameter
|
static OptionID |
MinKDistance.K_ID
OptionID for the "k" parameter.
|
static OptionID |
MinKDistance.KNNQUERY_ID
OptionID for the KNN query class to use (preprocessor, approximation, ...)
|
static OptionID |
LPNormDistanceFunction.P_ID
OptionID for the "p" parameter
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractSimilarityAdapter.SIMILARITY_FUNCTION_ID
Parameter to specify the similarity function to derive the distance between
database objects from.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
HSBHistogramQuadraticDistanceFunction.BPP_ID
Parameter for the kernel dimensionality.
|
static OptionID |
RGBHistogramQuadraticDistanceFunction.BPP_ID
Parameter for the kernel dimensionality.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
PCABasedCorrelationDistanceFunction.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 |
ERiCDistanceFunction.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 |
ERiCDistanceFunction.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.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
DistanceParser.DISTANCE_ID
Parameter for distance function.
|
static OptionID |
FileBasedDoubleDistanceFunction.MATRIX_ID
Parameter that specifies the name of the distance matrix file.
|
static OptionID |
FileBasedFloatDistanceFunction.MATRIX_ID
Parameter that specifies the name of the distance matrix file.
|
static OptionID |
DiskCacheBasedDoubleDistanceFunction.MATRIX_ID
Parameter that specifies the name of the distance matrix file.
|
static OptionID |
DiskCacheBasedFloatDistanceFunction.MATRIX_ID
Parameter that specifies the name of the distance matrix file.
|
static OptionID |
FileBasedDoubleDistanceFunction.PARSER_ID
Optional parameter to specify the parsers to provide a database, must
extend
DistanceParser . |
static OptionID |
FileBasedFloatDistanceFunction.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 |
DimensionSelectingDistanceFunction.DIM_ID
Parameter for dimensionality.
|
static OptionID |
AbstractDimensionsSelectingDoubleDistanceFunction.DIMS_ID
Dimensions parameter.
|
static OptionID |
AbstractPreferenceVectorBasedCorrelationDistanceFunction.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.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractEditDistanceFunction.BANDSIZE_ID
BANDSIZE parameter
|
static OptionID |
EDRDistanceFunction.DELTA_ID
DELTA parameter
|
static OptionID |
ERPDistanceFunction.G_ID
G parameter
|
static OptionID |
LCSSDistanceFunction.PDELTA_ID
PDELTA parameter
|
static OptionID |
LCSSDistanceFunction.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.DEGREE_ID
Degree parameter.
|
static OptionID |
FooKernelFunction.MAX_DEGREE_ID
Parameter for the maximum degree
|
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 |
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.MAX_K_ID
Maximum value for k
Key:
-precision.k
|
static OptionID |
OutlierROCCurve.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
JudgeOutlierScores.POSITIVE_CLASS_NAME_ID
The distance function to determine the reachability distance between
database objects.
|
static OptionID |
OutlierPrecisionRecallCurve.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
OutlierPrecisionAtKCurve.POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
static OptionID |
JudgeOutlierScores.SCALING_ID
Parameter to specify a scaling function to use.
|
static OptionID |
OutlierThresholdClustering.Parameterizer.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 |
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 |
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 |
PartitionApproximationMaterializeKNNPreprocessor.Factory.Parameterizer.SEED_ID
Parameter to specify the random number generator.
|
static OptionID |
RandomSampleKNNPreprocessor.Factory.Parameterizer.SEED_ID
Random number generator seed.
|
static OptionID |
RandomSampleKNNPreprocessor.Factory.Parameterizer.SHARE_ID
Parameter to specify how many objects to consider for computing the
kNN.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
RangeQueryFilteredPCAIndex.Factory.EPSILON_ID
Parameter to specify the maximum radius of the neighborhood to be
considered in the PCA, must be suitable to the distance function
specified.
|
static OptionID |
KNNQueryFilteredPCAIndex.Factory.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 |
PreDeConSubspaceIndex.Factory.DELTA_ID
Parameter for Delta.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
TreeIndexFactory.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 |
TreeIndexFactory.FILE_ID
Optional parameter that specifies the name of the file storing the index.
|
static OptionID |
TreeIndexFactory.PAGE_SIZE_ID
Parameter to specify the size of a page in bytes, must be an integer
greater than 0.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractMTreeFactory.DISTANCE_FUNCTION_ID
Parameter to specify the distance function to determine the distance
between database objects, must extend
DistanceFunction . |
Modifier and Type | Field and Description |
---|---|
static OptionID |
AbstractMkTreeUnifiedFactory.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 |
AbstractRStarTreeFactory.BULK_SPLIT_ID
Parameter for bulk strategy
|
static OptionID |
AbstractRStarTreeFactory.INSERTION_STRATEGY_ID
Fast-insertion parameter.
|
static OptionID |
AbstractRStarTreeFactory.MINIMUM_FILL_ID
Parameter for the relative minimum fill.
|
static OptionID |
AbstractRStarTreeFactory.OVERFLOW_STRATEGY_ID
Overflow treatment.
|
static OptionID |
AbstractRStarTreeFactory.SPLIT_STRATEGY_ID
Split strategy parameter.
|
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 |
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.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.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.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 |
KMLOutputHandler.Parameterizer.AUTOOPEN_ID
Parameter for automatically opening the output file.
|
static OptionID |
KMLOutputHandler.Parameterizer.COMPAT_ID
Parameter for compatibility mode.
|
static OptionID |
ResultWriter.GZIP_OUTPUT_ID
Flag to control GZIP compression.
|
static OptionID |
ResultWriter.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 |
EnsembleVotingRestrictedBayes.Parameterizer.MAX_ID
Option ID for the minimum and maximum vote
|
static OptionID |
EnsembleVotingBayes.Parameterizer.MIN_ID
Option ID for the minimum and maximum vote
|
static OptionID |
EnsembleVotingRestrictedBayes.Parameterizer.MIN_ID
Option ID for the minimum and maximum vote
|
static OptionID |
EnsembleVotingMedian.Parameterizer.QUANTILE_ID
Option ID for the quantile
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
OptionID.ALGORITHM
OptionID for
AlgorithmStep |
static OptionID |
OptionID.DATABASE
OptionID for
InputStep |
static OptionID |
OptionID.DATABASE_CONNECTION
OptionID for
InputStep |
static OptionID |
OptionID.DEBUG
Optional Parameter to specify a class to enable debugging for.
|
static OptionID |
OptionID.DESCRIPTION
Optional Parameter to specify a class to obtain a description for.
|
static OptionID |
OptionID.EVALUATOR
OptionID for
EvaluationStep |
static OptionID |
OptionID.HELP
Flag to obtain help-message.
|
static OptionID |
OptionID.HELP_LONG
Flag to obtain help-message.
|
static OptionID |
OptionID.OUTPUT
OptionID for the application output file/folder
|
static OptionID |
OptionID.RESULT_HANDLER
OptionID for
OutputStep |
static OptionID |
OptionID.TIME_FLAG
Flag to allow verbose messages while running the application.
|
static OptionID |
OptionID.VERBOSE_FLAG
Flag to allow verbose messages while running the application.
|
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 |
---|---|
Collection<Pair<OptionID,Object>> |
TrackParameters.getGivenParameters()
Get the tracked parameters that were actually set.
|
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.
|
DistanceParameter(OptionID optionID,
D dist)
Constructs a double parameter with the given optionID.
|
DistanceParameter(OptionID optionID,
D dist,
boolean optional)
Constructs a double parameter with the given optionID and optional flag.
|
DistanceParameter(OptionID optionID,
D dist,
D defaultValue)
Constructs a double parameter with the given optionID and default value.
|
DistanceParameter(OptionID optionID,
DistanceFunction<?,D> dist)
Constructs a double parameter with the given optionID.
|
DistanceParameter(OptionID optionID,
DistanceFunction<?,D> dist,
boolean optional)
Constructs a double parameter with the given optionID and optional flag.
|
DistanceParameter(OptionID optionID,
DistanceFunction<?,D> dist,
D defaultValue)
Constructs a double parameter with the given optionID 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,
boolean optional)
Deprecated.
Use
AbstractParameter.setOptional(boolean) instead. |
DoubleParameter(OptionID optionID,
double defaultValue)
Constructs a double parameter with the given optionID and default value.
|
DoubleParameter(OptionID optionID,
double defaultValue,
ParameterConstraint<Number> constraint)
|
DoubleParameter(OptionID optionID,
ParameterConstraint<Number> constraint)
|
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,
boolean optional)
Deprecated.
Use
AbstractParameter.setOptional(boolean) instead. |
IntParameter(OptionID optionID,
int defaultValue)
Constructs an integer parameter with the given optionID.
|
IntParameter(OptionID optionID,
int defaultValue,
ParameterConstraint<Number> constraint)
|
IntParameter(OptionID optionID,
ParameterConstraint<Number> constraint)
|
IntParameter(OptionID optionID,
ParameterConstraint<Number> constraint,
boolean optional)
|
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,
List<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.
|
LongParameter(OptionID optionID,
ParameterConstraint<Number> constraint,
long defaultValue)
|
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,
ParameterConstraint<String> constraint)
|
StringParameter(OptionID optionID,
ParameterConstraint<String> constraint,
String defaultValue)
|
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,
List<ParameterConstraint<List<List<Double>>>> constraints,
boolean optional)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
List<ParameterConstraint<List<List<Double>>>> constraints,
List<List<Double>> defaultValue)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
ParameterConstraint<List<List<Double>>> constraint)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
ParameterConstraint<List<List<Double>>> constraint,
boolean optional)
Constructs a vector list parameter with the given name and description.
|
VectorListParameter(OptionID optionID,
ParameterConstraint<List<List<Double>>> constraint,
List<List<Double>> defaultValue)
Constructs a vector list parameter with the given name and description.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
GridBasedReferencePoints.GRID_ID
Parameter to specify the grid resolution.
|
static OptionID |
GridBasedReferencePoints.GRID_SCALE_ID
Parameter to specify the extra scaling of the space, to allow
out-of-data-space reference points.
|
static OptionID |
RandomSampleReferencePoints.N_ID
Parameter to specify the sample size.
|
static OptionID |
RandomGeneratedReferencePoints.N_ID
Parameter to specify the number of requested reference points.
|
static OptionID |
StarBasedReferencePoints.NOCENTER_ID
Parameter to specify the grid resolution.
|
static OptionID |
RandomGeneratedReferencePoints.SCALE_ID
Parameter for additional scaling of the space, to allow out-of-space
reference points.
|
static OptionID |
StarBasedReferencePoints.SCALE_ID
Parameter to specify the extra scaling of the space, to allow
out-of-data-space reference points.
|
static OptionID |
AxisBasedReferencePoints.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.LAMBDA_ID
Parameter to specify the lambda value
Key:
-stddevscale.lambda
|
static OptionID |
SqrtStandardDeviationScaling.LAMBDA_ID
Parameter to specify the lambda value
Key:
-sqrtstddevscale.lambda
|
static OptionID |
OutlierLinearScaling.MAX_ID
Parameter to specify the maximum value.
|
static OptionID |
OutlierSqrtScaling.MAX_ID
Parameter to specify the fixed maximum to use.
|
static OptionID |
OutlierLinearScaling.MEAN_ID
Flag to use the mean as minimum for scaling.
|
static OptionID |
StandardDeviationScaling.MEAN_ID
Parameter to specify a fixed mean to use.
|
static OptionID |
SqrtStandardDeviationScaling.MEAN_ID
Parameter to specify a fixed mean to use.
|
static OptionID |
OutlierLinearScaling.MIN_ID
Parameter to specify a fixed minimum to use.
|
static OptionID |
OutlierSqrtScaling.MIN_ID
Parameter to specify the fixed minimum to use.
|
static OptionID |
SqrtStandardDeviationScaling.MIN_ID
Parameter to specify the 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.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
VisualizerParameterizer.ENABLEVIS_ID
Parameter to enable visualizers
Key: -vis.enable
Default: ELKI core
|
static OptionID |
ExportVisualizations.FOLDER_ID
Parameter to specify the output folder
Key:
-vis.output
|
static OptionID |
ExportVisualizations.RATIO_ID
Parameter to specify the canvas ratio
Key:
-vis.ratio
Default value: 1.33
|
static OptionID |
VisualizerParameterizer.SAMPLING_ID
Parameter to set the sampling level
Key: -vis.sampling
|
static OptionID |
VisualizerParameterizer.STYLELIB_ID
Parameter to get the style properties file.
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
ResultVisualizer.SINGLE_ID
Flag to set single display
Key: -vis.single
|
static OptionID |
ResultVisualizer.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.ROUNDED_ID
Currently unused option to enable/disable rounding
|
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.
|
static OptionID |
ClusterMeanVisualization.Parameterizer.STARS_ID
Option ID for visualization of cluster means.
|
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 |
MultiLPNorm.Parameterizer.EXPONENTS_ID
Option ID for the exponents
-multinorm.ps
|
Modifier and Type | Field and Description |
---|---|
static OptionID |
DistanceStddevOutlier.Parameterizer.K_ID
Option ID for parameterization.
|