| 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.
|
| 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.
|
| 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<? super O> distanceFunction,
int k,
double sample,
RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
protected RandomFactory |
ValidateApproximativeKNNIndex.random
Random generator factory
|
protected RandomFactory |
ValidateApproximativeKNNIndex.Parameterizer.random
Random generator factory
|
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
|
| 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 |
|---|---|
private RandomFactory |
XMeans.Parameterizer.random
Random number generator.
|
(package private) RandomFactory |
KMeansBatchedLloyd.random
Random used for partitioning.
|
(package private) RandomFactory |
KMeansBatchedLloyd.Parameterizer.random
Random used for partitioning.
|
(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 |
PROCLUS.rnd
Random generator
|
protected RandomFactory |
PROCLUS.Parameterizer.rnd
Random generator
|
private RandomFactory |
DOC.rnd
Randomizer used internally for sampling points.
|
| 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 |
FDBSCANNeighborPredicate.Parameterizer.seed
Random generator.
|
protected RandomFactory |
FDBSCAN.Parameterizer.seed
Random generator.
|
| Constructor and Description |
|---|
FDBSCAN(double epsilon,
int sampleSize,
double threshold,
RandomFactory seed,
int minpts)
Constructor that initialized GeneralizedDBSCAN.
|
FDBSCANNeighborPredicate.Instance(double epsilon,
int sampleSize,
double threshold,
Relation<? extends UncertainObject> relation,
RandomFactory rand)
Constructor.
|
FDBSCANNeighborPredicate(double epsilon,
int sampleSize,
double threshold,
RandomFactory seed)
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 |
DistanceQuantileSampler.rand
Random generator.
|
private RandomFactory |
DistanceQuantileSampler.Parameterizer.rand
Random generator.
|
protected RandomFactory |
RangeQuerySelectivity.random
Random sampling seed.
|
protected RandomFactory |
RangeQuerySelectivity.Parameterizer.random
Random sampling seed.
|
protected RandomFactory |
HopkinsStatisticClusteringTendency.random
Random generator seeding.
|
protected RandomFactory |
HopkinsStatisticClusteringTendency.Parameterizer.random
Random source.
|
protected RandomFactory |
EvaluateRetrievalPerformance.random
Random sampling seed.
|
private RandomFactory |
AveragePrecisionAtK.random
Random sampling seed.
|
protected RandomFactory |
EvaluateRetrievalPerformance.Parameterizer.seed
Random sampling seed.
|
protected RandomFactory |
AveragePrecisionAtK.Parameterizer.seed
Random sampling seed.
|
| Constructor and Description |
|---|
AveragePrecisionAtK(DistanceFunction<? super O> distanceFunction,
int k,
double sampling,
RandomFactory random,
boolean includeSelf)
Constructor.
|
DistanceQuantileSampler(DistanceFunction<? super O> distanceFunction,
double quantile,
double sampling,
boolean nozeros,
RandomFactory rand)
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.
|
RangeQuerySelectivity(DistanceFunction<? super V> distanceFunction,
double radius,
double sampling,
RandomFactory random)
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 |
|---|---|
private RandomFactory |
GeneratorXMLDatabaseConnection.Parameterizer.clusterRandom
Random generator used for initializing cluster generators.
|
protected RandomFactory |
RandomDoubleVectorDatabaseConnection.rnd
Random generator
|
(package private) RandomFactory |
RandomDoubleVectorDatabaseConnection.Parameterizer.rnd
Random generator.
|
| Constructor and Description |
|---|
GeneratorXMLDatabaseConnection(List<ObjectFilter> filters,
File specfile,
double sizescale,
Pattern reassign,
RandomFactory clusterRandom)
Constructor.
|
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 |
|---|---|
protected RandomFactory |
NumberVectorRandomFeatureSelectionFilter.rnd
Holds a random generator.
|
protected RandomFactory |
NumberVectorRandomFeatureSelectionFilter.Parameterizer.rnd
Random generator.
|
(package private) RandomFactory |
HistogramJitterFilter.Parameterizer.rnd
Random generator seed.
|
| 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 |
RandomProjectedNeighborsAndDensities.rnd
Random factory.
|
(package private) RandomFactory |
RandomProjectedNeighborsAndDensities.Parameterizer.rnd
Random factory.
|
| Constructor and Description |
|---|
RandomProjectedNeighborsAndDensities(RandomFactory rnd)
Constructor.
|
| Modifier and Type | Field and Description |
|---|---|
(package private) RandomFactory |
SpacefillingMaterializeKNNPreprocessor.Factory.random
Random number generator.
|
(package private) RandomFactory |
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.random
Random number generator.
|
(package private) RandomFactory |
SpacefillingKNNPreprocessor.Factory.random
Random number generator.
|
(package private) RandomFactory |
SpacefillingKNNPreprocessor.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 |
|---|
NaiveProjectedKNNPreprocessor.Factory(double window,
int projections,
RandomProjectionFamily proj,
RandomFactory random)
Constructor.
|
PartitionApproximationMaterializeKNNPreprocessor.Factory(int k,
DistanceFunction<? super O> distanceFunction,
int partitions,
RandomFactory rnd)
Constructor.
|
PartitionApproximationMaterializeKNNPreprocessor(Relation<O> relation,
DistanceFunction<? super O> distanceFunction,
int k,
int partitions,
RandomFactory rnd)
Constructor
|
RandomSampleKNNPreprocessor.Factory(int k,
DistanceFunction<? super O> distanceFunction,
double share,
RandomFactory rnd)
Constructor.
|
RandomSampleKNNPreprocessor(Relation<O> relation,
DistanceFunction<? super O> distanceFunction,
int k,
double share,
RandomFactory rnd)
Constructor.
|
SpacefillingKNNPreprocessor.Factory(List<SpatialSorter> curvegen,
double window,
int variants,
int odim,
RandomProjectionFamily proj,
RandomFactory random)
Constructor.
|
SpacefillingMaterializeKNNPreprocessor.Factory(int k,
DistanceFunction<? super V> distanceFunction,
List<SpatialSorter> curvegen,
double window,
int variants,
RandomFactory random)
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.
|
RandomSubsetProjectionFamily(RandomFactory random)
Constructor.
|
SimplifiedRandomHyperplaneProjectionFamily(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.