Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased |
Angle-based outlier detection algorithms.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise |
Normalizations operating on columns / variates; where each column is treated independently.
|
de.lmu.ifi.dbs.elki.evaluation.clustering |
Evaluation of clustering results.
|
de.lmu.ifi.dbs.elki.math |
Mathematical operations and utilities used throughout the framework.
|
de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator |
Estimators for statistical distributions.
|
de.lmu.ifi.dbs.elki.math.statistics.tests |
Statistical tests.
|
de.lmu.ifi.dbs.elki.utilities.datastructures.histogram |
Classes for computing histograms.
|
Modifier and Type | Field and Description |
---|---|
private MeanVariance |
FourCNeighborPredicate.mvCorDim
Tool to help with parameterization.
|
private MeanVariance |
PreDeConNeighborPredicate.mvSize
Tool to help with parameterization.
|
private MeanVariance |
FourCNeighborPredicate.mvSize
Tool to help with parameterization.
|
private MeanVariance |
FourCNeighborPredicate.mvSize2
Tool to help with parameterization.
|
private MeanVariance |
PreDeConNeighborPredicate.mvVar
Tool to help with parameterization.
|
Modifier and Type | Method and Description |
---|---|
protected double |
ABOD.computeABOF(KernelMatrix kernelMatrix,
DBIDRef pA,
DBIDArrayIter pB,
DBIDArrayIter pC,
MeanVariance s)
Compute the exact ABOF value.
|
Modifier and Type | Field and Description |
---|---|
(package private) MeanVariance[] |
AttributeWiseVarianceNormalization.mvs
Temporary storage used during initialization.
|
Modifier and Type | Method and Description |
---|---|
MeanVariance |
ClusterContingencyTable.averageSymmetricGini()
Compute the average Gini for each cluster (in both clusterings -
symmetric).
|
Modifier and Type | Class and Description |
---|---|
class |
MeanVarianceMinMax
Class collecting mean, variance, minimum and maximum statistics.
|
class |
StatisticalMoments
Track various statistical moments, including mean, variance, skewness and
kurtosis.
|
Modifier and Type | Method and Description |
---|---|
static MeanVariance[] |
MeanVariance.newArray(int dimensionality)
Create and initialize a new array of MeanVariance
|
MeanVariance |
MeanVariance.put(double[] vals)
Add values with weight 1.0
|
MeanVariance |
MeanVariance.put(double[] vals,
double[] weights) |
Constructor and Description |
---|
MeanVariance(MeanVariance other)
Constructor from other instance
|
Modifier and Type | Method and Description |
---|---|
LogNormalDistribution |
LogNormalLogMOMEstimator.estimateFromLogMeanVariance(MeanVariance mv,
double shift) |
LogGammaDistribution |
LogGammaLogMOMEstimator.estimateFromLogMeanVariance(MeanVariance mv,
double shift) |
abstract D |
AbstractLogMeanVarianceEstimator.estimateFromLogMeanVariance(MeanVariance mv,
double shift)
Estimate the distribution from mean and variance.
|
WaldDistribution |
WaldMOMEstimator.estimateFromMeanVariance(MeanVariance mv) |
NormalDistribution |
NormalMOMEstimator.estimateFromMeanVariance(MeanVariance mv) |
D |
MeanVarianceDistributionEstimator.estimateFromMeanVariance(MeanVariance mv)
Estimate the distribution from mean and variance.
|
GammaDistribution |
GammaMOMEstimator.estimateFromMeanVariance(MeanVariance mv) |
ExponentialDistribution |
ExponentialMOMEstimator.estimateFromMeanVariance(MeanVariance mv) |
abstract D |
AbstractMeanVarianceEstimator.estimateFromMeanVariance(MeanVariance mv) |
Modifier and Type | Method and Description |
---|---|
static int |
WelchTTest.calculateDOF(MeanVariance mv1,
MeanVariance mv2)
Calculates the degree of freedom according to Welch-Satterthwaite
|
static double |
WelchTTest.calculateTestStatistic(MeanVariance mv1,
MeanVariance mv2)
Calculate the statistic of Welch's t test using statistical moments of the
provided data samples
|
Modifier and Type | Field and Description |
---|---|
(package private) MeanVariance[] |
MeanVarianceStaticHistogram.data
Data store
|
Modifier and Type | Method and Description |
---|---|
protected MeanVariance |
MeanVarianceStaticHistogram.makeObject() |
Modifier and Type | Method and Description |
---|---|
void |
MeanVarianceStaticHistogram.putData(double coord,
MeanVariance data)
Aggregate new data into the histogram.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.