Package elki.index.tree.betula.features

Interface ClusterFeature

All Superinterfaces:

AsClusterFeature, FeatureVector<java.lang.Number>, NumberVector, SpatialComparable

All Known Implementing Classes:

BIRCHCF, VIIFeature, VVIFeature, VVVFeature

public interface ClusterFeature
extends AsClusterFeature, NumberVector

Interface for basic ClusteringFeature functions

Since:

0.8.0

Author:

Andreas Lang

Nested Class Summary

Nested Classes

Modifier and Type	Interface	Description
static interface	ClusterFeature.Factory<F extends ClusterFeature>	Cluster feature factory

Field Summary

Fields inherited from interface elki.data.FeatureVector

TYPE

Fields inherited from interface elki.data.NumberVector

ATTRIBUTE_SEPARATOR, FIELD, FIELD_1D, FIELD_2D, VARIABLE_LENGTH

Method Summary

Modifier and Type	Method	Description
void	addToStatistics(NumberVector nv)	Add NumberVector to CF
void	addToStatistics(ClusterFeature other)	Add other CF to CF
double	centroid(int d)	Returns the mean of the specified dimension.
double[][]	covariance()	returns the covariance matrix
default double	doubleValue(int dimension)	Returns the value in the specified dimension as double.
default ClusterFeature	getCF()	Get as clustering feature.
int	getWeight()	Return the weight
default long	longValue(int dimension)	Returns the value in the specified dimension as long.
void	resetStatistics()	Resets all statistics of CF
double	sumdev()	Returns the total sum of Deviations.
double	variance()	Returns the total variance.
double	variance(int d)	Returns the variance in the specified dimension.

Methods inherited from interface elki.data.FeatureVector

getDimensionality, toString

Methods inherited from interface elki.data.NumberVector

byteValue, floatValue, getMax, getMin, getValue, intValue, shortValue, toArray

Methods inherited from interface elki.data.spatial.SpatialComparable

getDimensionality

Method Detail

addToStatistics

void addToStatistics(NumberVector nv)

Add NumberVector to CF

Parameters:

nv - NumberVector

addToStatistics

void addToStatistics(ClusterFeature other)

Add other CF to CF

Parameters:

other - other CF

resetStatistics

void resetStatistics()

Resets all statistics of CF

getWeight

int getWeight()

Return the weight

Returns:

weight of CF

centroid

double centroid(int d)

Returns the mean of the specified dimension.

Parameters:

d - dimension

Returns:

mean of this dimension

doubleValue

default double doubleValue(int dimension)

Description copied from interface: NumberVector

Returns the value in the specified dimension as double.

Note: this might seem redundant with respect to getValue(dim).doubleValue(), but usually this is much more efficient due to boxing/unboxing cost.

Specified by:

doubleValue in interface NumberVector

Parameters:

dimension - the desired dimension, where 0 ≤ dimension < this.getDimensionality()

Returns:

the value in the specified dimension

longValue

default long longValue(int dimension)

Description copied from interface: NumberVector

Returns the value in the specified dimension as long.

Note: this might seem redundant with respect to getValue(dim).longValue(), but usually this is much more efficient due to boxing/unboxing cost.

Specified by:

longValue in interface NumberVector

Parameters:

dimension - the desired dimension, where 0 ≤ dimension < this.getDimensionality()

Returns:

the value in the specified dimension

variance

double variance()

Returns the total variance.

Returns:

variance.

sumdev

double sumdev()

Returns the total sum of Deviations.

Returns:

Sum of Deviations.

variance

double variance(int d)

Returns the variance in the specified dimension.

Parameters:

d - dimension

Returns:

variance in this dimension.

covariance

double[][] covariance()

returns the covariance matrix

Returns:

covariance

getCF

default ClusterFeature getCF()

Description copied from interface: AsClusterFeature

Get as clustering feature.

Specified by:

getCF in interface AsClusterFeature

Returns:

Clustering feature