Package | Description |
---|---|
de.lmu.ifi.dbs.elki.datasource.filter.normalization |
Data normalization.
|
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.tests |
Statistical tests.
|
de.lmu.ifi.dbs.elki.utilities.datastructures.histogram |
Classes for computing histograms.
|
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.
|
Modifier and Type | Method and Description |
---|---|
static MeanVariance[] |
MeanVariance.newArray(int dimensionality)
Create and initialize a new array of MeanVariance
|
Constructor and Description |
---|
MeanVariance(MeanVariance other)
Constructor from other instance
|
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.
|