Uses of Class
elki.math.MeanVariance

Packages that use MeanVariance

Package	Description
elki.application.benchmark	Benchmarking pseudo algorithms.
elki.clustering.dbscan.predicates	Neighbor and core predicated for Generalized DBSCAN.
elki.datasource.filter.normalization.columnwise	Normalizations operating on columns / variates; where each column is treated independently.
elki.evaluation.clustering	Evaluation of clustering results.
elki.math	Mathematical operations and utilities used throughout the framework.
elki.math.statistics.distribution.estimator	Estimators for statistical distributions.
elki.outlier.anglebased	Angle-based outlier detection algorithms.

Uses of MeanVariance in elki.application.benchmark

Methods in elki.application.benchmark with parameters of type MeanVariance

Modifier and Type	Method	Description
protected int	RangeQueryBenchmark.processResult(DoubleDBIDList rres, MeanVariance mv)	Method to test a result.
private int	KNNBenchmark.run(KNNSearcher<DBIDRef> knnQuery, Relation<O> relation, Duration dur, MeanVariance mv, MeanVariance mvdist)	Run with the database as query source
private int	KNNBenchmark.run(KNNSearcher<O> knnQuery, Duration dur, MeanVariance mv, MeanVariance mvdist)	Run using a second database as query source
private int	PrioritySearchBenchmark.run(PrioritySearcher<DBIDRef> priQuery, Relation<O> relation, Duration dur, MeanVariance mv, MeanVariance mvdist)	Run with the database as query source
private int	PrioritySearchBenchmark.run(PrioritySearcher<O> priQuery, Duration dur, MeanVariance mv, MeanVariance mvdist)	Run using a second database as query source
protected int	RangeQueryBenchmark.run(RangeSearcher<DBIDRef> rangeQuery, Relation<O> relation, double radius, Duration dur, MeanVariance mv)	Run the algorithm, with constant radius
protected int	RangeQueryBenchmark.run(RangeSearcher<DBIDRef> rangeQuery, Relation<O> relation, Relation<NumberVector> radrel, Duration dur, MeanVariance mv)	Run the algorithm, with separate radius relation
protected int	RangeQueryBenchmark.run(RangeSearcher<O> rangeQuery, Relation<O> relation, DatabaseConnection queries, Duration dur, MeanVariance mv)	Run the algorithm, with a separate query set.

Uses of MeanVariance in elki.clustering.dbscan.predicates

Fields in elki.clustering.dbscan.predicates declared as MeanVariance

Modifier and Type	Field	Description
private MeanVariance	FourCNeighborPredicate.mvCorDim	Tool to help with parameterization.
private MeanVariance	FourCNeighborPredicate.mvSize	Tool to help with parameterization.
private MeanVariance	PreDeConNeighborPredicate.mvSize	Tool to help with parameterization.
private MeanVariance	FourCNeighborPredicate.mvSize2	Tool to help with parameterization.
private MeanVariance	PreDeConNeighborPredicate.mvVar	Tool to help with parameterization.

Uses of MeanVariance in elki.datasource.filter.normalization.columnwise

Fields in elki.datasource.filter.normalization.columnwise declared as MeanVariance

Modifier and Type	Field	Description
(package private) MeanVariance[]	AttributeWiseVarianceNormalization.mvs	Temporary storage used during initialization.

Uses of MeanVariance in elki.evaluation.clustering

Methods in elki.evaluation.clustering that return MeanVariance

Modifier and Type	Method	Description
MeanVariance	ClusterContingencyTable.adjustedSymmetricGini()	Compute the adjusted average Gini for each cluster (in both clusterings - symmetric).
MeanVariance	ClusterContingencyTable.averageSymmetricGini()	Compute the average Gini for each cluster (in both clusterings - symmetric).

Uses of MeanVariance in elki.math

Subclasses of MeanVariance in elki.math

Modifier and Type	Class	Description
class	MeanVarianceMinMax	Class collecting mean, variance, minimum and maximum statistics.
class	StatisticalMoments	Track various statistical moments, including mean, variance, skewness and kurtosis.

Methods in elki.math that return MeanVariance

Modifier and Type	Method	Description
static MeanVariance[]	MeanVariance.newArray(int dimensionality)	Create and initialize a new array of MeanVariance.
static MeanVariance[]	MeanVariance.of(Relation<? extends NumberVector> relation)	Compute the variances of a relation.
MeanVariance	MeanVariance.put(double[] vals)	Add values with weight 1.0
MeanVariance	MeanVariance.put(double[] vals, double[] weights)
MeanVariance	MeanVarianceMinMax.put(double[] vals, double[] weights)
MeanVariance	MeanVariance.reset()

Constructors in elki.math with parameters of type MeanVariance

Constructor	Description
MeanVariance(MeanVariance other)	Constructor from other instance

Uses of MeanVariance in elki.math.statistics.distribution.estimator

Methods in elki.math.statistics.distribution.estimator with parameters of type MeanVariance

Modifier and Type	Method	Description
ExpGammaDistribution	ExpGammaExpMOMEstimator.estimateFromExpMeanVariance(MeanVariance mv)
D	LogMeanVarianceEstimator.estimateFromLogMeanVariance(MeanVariance mv, double shift)	Estimate the distribution from mean and variance.
LogNormalDistribution	LogNormalLogMOMEstimator.estimateFromLogMeanVariance(MeanVariance mv, double shift)
ExponentialDistribution	ExponentialMOMEstimator.estimateFromMeanVariance(MeanVariance mv)
GammaDistribution	GammaMOMEstimator.estimateFromMeanVariance(MeanVariance mv)
InverseGaussianDistribution	InverseGaussianMOMEstimator.estimateFromMeanVariance(MeanVariance mv)
D	MeanVarianceDistributionEstimator.estimateFromMeanVariance(MeanVariance mv)	Estimate the distribution from mean and variance.
NormalDistribution	NormalMOMEstimator.estimateFromMeanVariance(MeanVariance mv)

Uses of MeanVariance in elki.outlier.anglebased

Methods in elki.outlier.anglebased with parameters of type MeanVariance

Modifier and Type	Method	Description
protected double	ABOD.computeABOF(KernelMatrix kernelMatrix, DBIDRef pA, DBIDArrayIter pB, DBIDArrayIter pC, MeanVariance s)	Compute the exact ABOF value.