| 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.correlation |
Correlation clustering algorithms
|
| 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.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.uncertain |
Clustering algorithms for uncertain data.
|
| 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.subspace |
Subspace outlier detection methods.
|
| 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.experiments |
Packaged experiments to make them easy to reproduce.
|
| de.lmu.ifi.dbs.elki.database.ids |
Database object identification and ID group handling API.
|
| de.lmu.ifi.dbs.elki.datasource |
Data normalization (and reconstitution) of data sets.
|
| 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.evaluation.classification.holdout |
Holdout and cross-validation strategies for evaluating classifiers.
|
| 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.projected |
Projected indexes for data.
|
| 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.math.dimensionsimilarity |
Functions to compute the similarity of dimensions (or the interestingness of the combination).
|
| 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.random |
Random number generation.
|
| de.lmu.ifi.dbs.elki.math.statistics.dependence |
Statistical measures of dependence, such as correlation.
|
| de.lmu.ifi.dbs.elki.math.statistics.distribution |
Standard distributions, with random generation functionalities.
|
| de.lmu.ifi.dbs.elki.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.visualization |
Visualization package of ELKI.
|
| de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain |
Visualizers for uncertain data.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
KNNDistancesSampler.rnd
Random number seeding.
|
private RandomFactory |
KNNDistancesSampler.Parameterizer.rnd
Random number seeding.
|
| Constructor and Description |
|---|
KNNDistancesSampler(DistanceFunction<O> distanceFunction,
int k,
double sample,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
RangeQueryBenchmarkAlgorithm.random
Random generator factory
|
protected RandomFactory |
RangeQueryBenchmarkAlgorithm.Parameterizer.random
Random generator factory
|
protected RandomFactory |
KNNBenchmarkAlgorithm.random
Random generator factory
|
protected RandomFactory |
KNNBenchmarkAlgorithm.Parameterizer.random
Random generator factory
|
protected RandomFactory |
ValidateApproximativeKNNIndex.random
Random generator factory
|
protected RandomFactory |
ValidateApproximativeKNNIndex.Parameterizer.random
Random generator factory
|
| Constructor and Description |
|---|
KNNBenchmarkAlgorithm(DistanceFunction<? super O> distanceFunction,
int k,
DatabaseConnection queries,
double sampling,
RandomFactory random)
Constructor.
|
RangeQueryBenchmarkAlgorithm(DistanceFunction<? super O> distanceFunction,
DatabaseConnection queries,
double sampling,
RandomFactory random)
Constructor.
|
ValidateApproximativeKNNIndex(DistanceFunction<? super O> distanceFunction,
int k,
DatabaseConnection queries,
double sampling,
boolean forcelinear,
RandomFactory random,
Pattern pattern)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
ORCLUS.rnd
Random generator
|
protected RandomFactory |
ORCLUS.Parameterizer.rnd |
private RandomFactory |
LMCLUS.rnd
Random factory
|
private RandomFactory |
LMCLUS.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
LMCLUS(int maxdim,
int minsize,
int samplingLevel,
double sensitivityThreshold,
RandomFactory rnd)
Constructor.
|
ORCLUS(int k,
int k_i,
int l,
double alpha,
RandomFactory rnd,
PCARunner pca)
Java constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
KMeansBatchedLloyd.random
Random used for partitioning.
|
(package private) RandomFactory |
KMeansBatchedLloyd.Parameterizer.random
Random used for partitioning.
|
private RandomFactory |
XMeans.Parameterizer.random
Random number generator.
|
(package private) RandomFactory |
CLARA.random
Random factory for initialization.
|
(package private) RandomFactory |
CLARA.Parameterizer.random
Random factory for initialization.
|
(package private) RandomFactory |
XMeans.rnd
Random factory.
|
| Constructor and Description |
|---|
CLARA(DistanceFunction<? super V> distanceFunction,
int k,
int maxiter,
KMedoidsInitialization<V> initializer,
int numsamples,
double sampling,
RandomFactory random)
Constructor.
|
KMeansBatchedLloyd(NumberVectorDistanceFunction<? super V> distanceFunction,
int k,
int maxiter,
KMeansInitialization<? super V> initializer,
int blocks,
RandomFactory random)
Constructor.
|
XMeans(NumberVectorDistanceFunction<? super V> distanceFunction,
int k_min,
int k_max,
int maxiter,
KMeans<V,M> innerKMeans,
KMeansInitialization<? super V> initializer,
PredefinedInitialMeans splitInitializer,
KMeansQualityMeasure<V> informationCriterion,
RandomFactory random)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
AbstractKMeansInitialization.rnd
Random number generator
|
protected RandomFactory |
AbstractKMeansInitialization.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
AbstractKMeansInitialization(RandomFactory rnd)
Constructor.
|
FarthestPointsInitialMeans(RandomFactory rnd,
boolean dropfirst)
Constructor.
|
FarthestSumPointsInitialMeans(RandomFactory rnd,
boolean dropfirst)
Constructor.
|
KMeansPlusPlusInitialMeans(RandomFactory rnd)
Constructor.
|
RandomlyChosenInitialMeans(RandomFactory rnd)
Constructor.
|
RandomlyGeneratedInitialMeans(RandomFactory rnd)
Constructor.
|
SampleKMeansInitialization(RandomFactory rnd,
KMeans<V,?> innerkMeans,
double rate)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
DOC.Parameterizer.random
Random seeding factory.
|
private RandomFactory |
DOC.rnd
Randomizer used internally for sampling points.
|
private RandomFactory |
PROCLUS.rnd
Random generator
|
protected RandomFactory |
PROCLUS.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
DOC(double alpha,
double beta,
double w,
boolean heuristics,
int d_zero,
RandomFactory random)
Constructor.
|
PROCLUS(int k,
int k_i,
int l,
int m_i,
RandomFactory rnd)
Java constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
FDBSCANNeighborPredicate.rand
The
Random object to draw the samples with. |
protected RandomFactory |
RepresentativeUncertainClustering.random
Random factory for sampling.
|
protected RandomFactory |
RepresentativeUncertainClustering.Parameterizer.random
Random factory for sampling.
|
protected RandomFactory |
UKMeans.rnd
Our Random factory
|
protected RandomFactory |
UKMeans.Parameterizer.rnd
Our Random factory
|
protected RandomFactory |
FDBSCAN.Parameterizer.seed
Random generator.
|
protected RandomFactory |
FDBSCANNeighborPredicate.Parameterizer.seed
Random generator.
|
| Constructor and Description |
|---|
FDBSCAN(double epsilon,
int sampleSize,
double threshold,
RandomFactory seed,
int minpts)
Constructor that initialized GeneralizedDBSCAN.
|
FDBSCANNeighborPredicate(double epsilon,
int sampleSize,
double threshold,
RandomFactory seed)
Constructor.
|
Instance(double epsilon,
int sampleSize,
double threshold,
Relation<? extends UncertainObject> relation,
RandomFactory rand)
Constructor.
|
RepresentativeUncertainClustering(ClusteringDistanceSimilarityFunction distance,
ClusteringAlgorithm<?> metaAlgorithm,
ClusteringAlgorithm<?> samplesAlgorithm,
int numsamples,
RandomFactory random,
double alpha,
boolean keep)
Constructor, quite trivial.
|
UKMeans(int k,
int maxiter,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
ALOCI.rnd
Random generator
|
protected RandomFactory |
ALOCI.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
ALOCI(NumberVectorDistanceFunction<?> distanceFunction,
int nmin,
int alpha,
int g,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
HiCS.rnd
Random generator.
|
private RandomFactory |
HiCS.Parameterizer.rnd
Random generator.
|
private RandomFactory |
FeatureBagging.rnd
Random number generator for subspace choice.
|
protected RandomFactory |
FeatureBagging.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
FeatureBagging(int k,
int num,
boolean breadth,
RandomFactory rnd)
Constructor.
|
HiCS(int m,
double alpha,
OutlierAlgorithm outlierAlgorithm,
GoodnessOfFitTest statTest,
int cutoff,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
AggarwalYuEvolutionary.rnd
Random generator.
|
protected RandomFactory |
AggarwalYuEvolutionary.Parameterizer.rnd |
| Constructor and Description |
|---|
AggarwalYuEvolutionary(int k,
int phi,
int m,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
AveragePrecisionAtK.random
Random sampling seed.
|
private RandomFactory |
EvaluateRetrievalPerformance.random
Random sampling seed.
|
private RandomFactory |
HopkinsStatisticClusteringTendency.random
Random generator seeding.
|
protected RandomFactory |
HopkinsStatisticClusteringTendency.Parameterizer.random
Random source.
|
protected RandomFactory |
AveragePrecisionAtK.Parameterizer.seed
Random sampling seed.
|
protected RandomFactory |
EvaluateRetrievalPerformance.Parameterizer.seed
Random sampling seed.
|
| Constructor and Description |
|---|
AveragePrecisionAtK(DistanceFunction<? super O> distanceFunction,
int k,
double sampling,
RandomFactory random,
boolean includeSelf)
Constructor.
|
EvaluateRetrievalPerformance(DistanceFunction<? super O> distanceFunction,
double sampling,
RandomFactory random,
boolean includeSelf,
int maxk)
Constructor.
|
HopkinsStatisticClusteringTendency(NumberVectorDistanceFunction<? super NumberVector> distanceFunction,
int samplesize,
RandomFactory random,
int rep,
int k,
double[] minima,
double[] maxima)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
EvaluateIntrinsicDimensionalityEstimators.rnd
Random generator.
|
(package private) RandomFactory |
EvaluateIntrinsicDimensionalityEstimators.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
EvaluateIntrinsicDimensionalityEstimators(int startk,
int maxk,
int samples,
int dim,
EvaluateIntrinsicDimensionalityEstimators.Aggregate agg,
EvaluateIntrinsicDimensionalityEstimators.OutputFormat format,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Method and Description |
|---|---|
static DBIDs |
DBIDUtil.randomSample(DBIDs ids,
double rate,
RandomFactory random)
Produce a random sample of the given DBIDs.
|
static ModifiableDBIDs |
DBIDUtil.randomSample(DBIDs source,
int k,
RandomFactory rnd)
Produce a random sample of the given DBIDs.
|
static DBIDVar |
DBIDUtil.randomSample(DBIDs ids,
RandomFactory random)
Draw a single random sample.
|
static void |
DBIDUtil.randomShuffle(ArrayModifiableDBIDs ids,
RandomFactory rnd)
Produce a random shuffling of the given DBID array.
|
static ArrayDBIDs[] |
DBIDUtil.randomSplit(DBIDs ids,
int p,
RandomFactory rnd)
Randomly split IDs into
p partitions of almost-equal size. |
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
RandomDoubleVectorDatabaseConnection.rnd
Random generator
|
(package private) RandomFactory |
RandomDoubleVectorDatabaseConnection.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
RandomDoubleVectorDatabaseConnection(int dim,
int size,
RandomFactory rnd,
List<ObjectFilter> filters)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
ShuffleObjectsFilter.rnd
Random generator.
|
(package private) RandomFactory |
ShuffleObjectsFilter.Parameterizer.rnd
Random generator
|
protected RandomFactory |
RandomSamplingStreamFilter.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
RandomSamplingStreamFilter(double prob,
RandomFactory rnd)
Constructor.
|
ShuffleObjectsFilter(RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
HistogramJitterFilter.Parameterizer.rnd
Random generator seed.
|
protected RandomFactory |
NumberVectorRandomFeatureSelectionFilter.rnd
Holds a random generator.
|
protected RandomFactory |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
HistogramJitterFilter(double jitter,
RandomFactory rnd)
Constructor.
|
NumberVectorRandomFeatureSelectionFilter(int dim,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
UncertainifyFilter.Parameterizer.rand
Random generator.
|
| Constructor and Description |
|---|
UncertainifyFilter(Uncertainifier<UO> generator,
boolean keep,
RandomFactory randf)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
RandomizedHoldout.random
The random generator.
|
protected RandomFactory |
RandomizedHoldout.Parameterizer.random
The random generator.
|
| Constructor and Description |
|---|
DisjointCrossValidation(RandomFactory random,
int nfold)
Constructor.
|
RandomizedCrossValidation(RandomFactory random,
int nfold)
Constructor for n-fold cross-validation.
|
RandomizedHoldout(RandomFactory random)
Sets the parameter seed to the parameterToDescription map.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
CosineHashFunctionFamily.Parameterizer.random
Random generator to use.
|
protected RandomFactory |
AbstractProjectedHashFunctionFamily.random
Random generator to use.
|
(package private) RandomFactory |
AbstractProjectedHashFunctionFamily.Parameterizer.random
Random generator to use.
|
| Constructor and Description |
|---|
AbstractProjectedHashFunctionFamily(RandomFactory random,
RandomProjectionFamily proj,
double width,
int k)
Constructor.
|
CosineHashFunctionFamily(int k,
RandomFactory random)
Constructor.
|
EuclideanHashFunctionFamily(RandomFactory random,
double width,
int k)
Constructor.
|
ManhattanHashFunctionFamily(RandomFactory random,
double width,
int k)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
RandomProjectedNeighborssAndDensities.rnd
Random factory.
|
(package private) RandomFactory |
RandomProjectedNeighborssAndDensities.Parameterizer.rnd
Random factory.
|
| Constructor and Description |
|---|
RandomProjectedNeighborssAndDensities(RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
SpacefillingKNNPreprocessor.Factory.random
Random number generator.
|
(package private) RandomFactory |
SpacefillingKNNPreprocessor.Factory.Parameterizer.random
Random number generator.
|
(package private) RandomFactory |
SpacefillingMaterializeKNNPreprocessor.Factory.random
Random number generator.
|
(package private) RandomFactory |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.random
Random number generator.
|
(package private) RandomFactory |
NaiveProjectedKNNPreprocessor.Factory.random
Random number generator.
|
(package private) RandomFactory |
NaiveProjectedKNNPreprocessor.Factory.Parameterizer.random
Random number generator.
|
private RandomFactory |
RandomSampleKNNPreprocessor.rnd
Random generator
|
private RandomFactory |
RandomSampleKNNPreprocessor.Factory.rnd
Random generator
|
private RandomFactory |
RandomSampleKNNPreprocessor.Factory.Parameterizer.rnd
Random generator
|
private RandomFactory |
PartitionApproximationMaterializeKNNPreprocessor.rnd
Random generator
|
private RandomFactory |
PartitionApproximationMaterializeKNNPreprocessor.Factory.rnd
Random generator
|
private RandomFactory |
PartitionApproximationMaterializeKNNPreprocessor.Factory.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
Factory(double window,
int projections,
RandomProjectionFamily proj,
RandomFactory random)
Constructor.
|
Factory(int k,
DistanceFunction<? super O> distanceFunction,
double share,
RandomFactory rnd)
Constructor.
|
Factory(int k,
DistanceFunction<? super O> distanceFunction,
int partitions,
RandomFactory rnd)
Constructor.
|
Factory(int k,
DistanceFunction<? super V> distanceFunction,
List<SpatialSorter> curvegen,
double window,
int variants,
RandomFactory random)
Constructor.
|
Factory(List<SpatialSorter> curvegen,
double window,
int variants,
int odim,
RandomProjectionFamily proj,
RandomFactory random)
Constructor.
|
PartitionApproximationMaterializeKNNPreprocessor(Relation<O> relation,
DistanceFunction<? super O> distanceFunction,
int k,
int partitions,
RandomFactory rnd)
Constructor
|
RandomSampleKNNPreprocessor(Relation<O> relation,
DistanceFunction<? super O> distanceFunction,
int k,
double share,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
PINN.Parameterizer.random
Random generator.
|
| Constructor and Description |
|---|
PINN(IndexFactory<O,?> inner,
int t,
double s,
double h,
RandomFactory random)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
RandomSplit.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
RandomSplit(RandomFactory rnd)
Creates a new split object.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
HiCSDimensionSimilarity.rnd
Random generator
|
private RandomFactory |
HiCSDimensionSimilarity.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
HiCSDimensionSimilarity(GoodnessOfFitTest statTest,
int m,
double alpha,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
RANSACCovarianceMatrixBuilder.rnd
Random generator
|
(package private) RandomFactory |
RANSACCovarianceMatrixBuilder.Parameterizer.rnd
Random generator
|
| Constructor and Description |
|---|
RANSACCovarianceMatrixBuilder(int iterations,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
AbstractRandomProjectionFamily.Parameterizer.random
Random generator.
|
| Constructor and Description |
|---|
AbstractRandomProjectionFamily(RandomFactory random)
Constructor.
|
AchlioptasRandomProjectionFamily(double sparsity,
RandomFactory random)
Constructor.
|
CauchyRandomProjectionFamily(RandomFactory random)
Constructor.
|
GaussianRandomProjectionFamily(RandomFactory random)
Constructor.
|
RandomHyperplaneProjectionFamily(RandomFactory random)
Constructor.
|
RandomSubsetProjectionFamily(RandomFactory random)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
static RandomFactory |
RandomFactory.DEFAULT
Global default factory
|
| Modifier and Type | Method and Description |
|---|---|
static RandomFactory |
RandomFactory.get(Long seed)
Factory method: Get a random factory for the given seed.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
HiCSDependenceMeasure.rnd
Random generator
|
private RandomFactory |
HiCSDependenceMeasure.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
HiCSDependenceMeasure(GoodnessOfFitTest statTest,
int m,
double alpha,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
AbstractDistribution.Parameterizer.rnd
Random source.
|
| Constructor and Description |
|---|
AbstractDistribution(RandomFactory rnd)
Constructor.
|
BetaDistribution(double a,
double b,
RandomFactory random)
Constructor.
|
CauchyDistribution(double location,
double shape,
RandomFactory random)
Constructor.
|
ChiDistribution(double dof,
RandomFactory random)
Constructor.
|
ChiSquaredDistribution(double dof,
RandomFactory random)
Constructor.
|
ExponentialDistribution(double rate,
double location,
RandomFactory random)
Constructor.
|
ExponentiallyModifiedGaussianDistribution(double mean,
double stddev,
double lambda,
RandomFactory random)
Constructor for ExGaussian distribution
|
GammaDistribution(double k,
double theta,
RandomFactory random)
Constructor for Gamma distribution.
|
GeneralizedExtremeValueDistribution(double mu,
double sigma,
double k,
RandomFactory random)
Constructor.
|
GeneralizedLogisticAlternateDistribution(double location,
double scale,
double shape,
RandomFactory random)
Constructor.
|
GeneralizedLogisticDistribution(double location,
double scale,
double shape,
RandomFactory random)
Constructor.
|
GeneralizedParetoDistribution(double mu,
double sigma,
double xi,
RandomFactory random)
Constructor.
|
GumbelDistribution(double mu,
double beta,
RandomFactory random)
Constructor.
|
HaltonUniformDistribution(double min,
double max,
RandomFactory rnd)
Constructor for a halton pseudo uniform distribution on the interval [min,
max[
|
KappaDistribution(double location,
double scale,
double shape1,
double shape2,
RandomFactory random)
Constructor.
|
LaplaceDistribution(double rate,
double location,
RandomFactory random)
Constructor.
|
LogGammaAlternateDistribution(double k,
double theta,
double shift,
RandomFactory random)
Constructor for Gamma distribution.
|
LogGammaDistribution(double k,
double theta,
double shift,
RandomFactory random)
Constructor for Gamma distribution.
|
LogisticDistribution(double location,
double scale,
RandomFactory random)
Constructor.
|
LogLogisticDistribution(double scale,
double shape,
RandomFactory random)
Constructor.
|
LogNormalDistribution(double logmean,
double logstddev,
double shift,
RandomFactory random)
Constructor for Log-Normal distribution
|
NormalDistribution(double mean,
double stddev,
RandomFactory random)
Constructor for Gaussian distribution
|
PoissonDistribution(int n,
double p,
RandomFactory random)
Constructor.
|
RayleighDistribution(double mu,
double sigma,
RandomFactory random)
Constructor.
|
SkewGeneralizedNormalDistribution(double mean,
double stddev,
double skew,
RandomFactory random)
Constructor for Gaussian distribution
|
StudentsTDistribution(int v,
RandomFactory random)
Constructor.
|
UniformDistribution(double min,
double max,
RandomFactory random)
Constructor for a uniform distribution on the interval [min, max[
|
WaldDistribution(double mean,
double shape,
RandomFactory random)
Constructor for wald distribution
|
WeibullDistribution(double k,
double lambda,
double theta,
RandomFactory random)
Constructor.
|
| Modifier and Type | Method and Description |
|---|---|
protected RandomFactory |
RandomParameter.parseValue(Object obj) |
| Constructor and Description |
|---|
RandomParameter(OptionID optionID,
RandomFactory defaultValue)
Constructor with default value.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
RandomSampleReferencePoints.rnd
Random generator.
|
protected RandomFactory |
RandomSampleReferencePoints.Parameterizer.rnd
Random generator.
|
protected RandomFactory |
RandomGeneratedReferencePoints.rnd
Random generator.
|
protected RandomFactory |
RandomGeneratedReferencePoints.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
RandomGeneratedReferencePoints(int samplesize,
double scale,
RandomFactory rnd)
Constructor.
|
RandomSampleReferencePoints(int samplesize,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
private RandomFactory |
VisualizerParameterizer.rnd
Random seed for sampling.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
UncertainSamplesVisualization.Instance.random
Random factory.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.