FeatureExtractor.Clustering
Class ClusteringFeatures

java.lang.Object
  FeatureExtractor.Clustering.ClusteringFeatures

Direct Known Subclasses:

WindsurfClusteringFeatures

public abstract class ClusteringFeatures
extends java.lang.Object

Abstract class representing the clustering features.

Constructor Summary

ClusteringFeatures()

Method Summary

abstract void	clear() Clears the features of this object.
abstract ClusteringFeatures	clone() Creates a new ClusteringFeatures object as a copy of this object.
static ClusteringFeatures	computeCentroid(java.util.Vector<ClusteringFeatures> v) Computes the centroid of a vector of ClusteringFeatures.
abstract ClusteringFeatures	diff(ClusteringFeatures p) Subtracts the features of a given object to those of this object.
abstract ClusteringFeatures	normalize(double n) Normalizes the features of this object.
abstract int	size() Returns the number of features for this object.
abstract ClusteringFeatures	sum(ClusteringFeatures p) Adds the features of this object to those of a given object.

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ClusteringFeatures

public ClusteringFeatures()

Method Detail

computeCentroid

public static ClusteringFeatures computeCentroid(java.util.Vector<ClusteringFeatures> v)

Computes the centroid of a vector of ClusteringFeatures.

Parameters:

v - The vector of ClusteringFeatures.

Returns:

A new ClusteringFeatures object computed as the centroid of given features.

clone

public abstract ClusteringFeatures clone()

Creates a new ClusteringFeatures object as a copy of this object.

Overrides:

clone in class java.lang.Object

Returns:

A new ClusteringFeatures object.

clear

public abstract void clear()

Clears the features of this object.

sum

public abstract ClusteringFeatures sum(ClusteringFeatures p)

Adds the features of this object to those of a given object.

Parameters:

p - The features to be added.

Returns:

A new ClusteringFeatures object as the sum of the two objects.

diff

public abstract ClusteringFeatures diff(ClusteringFeatures p)

Subtracts the features of a given object to those of this object.

Parameters:

p - The features to be subtracted.

Returns:

A new ClusteringFeatures object as the difference of the two objects.

normalize

public abstract ClusteringFeatures normalize(double n)

Normalizes the features of this object.

Parameters:

n - The value used to normalize the features.

Returns:

A new ClusteringFeatures object with normalized features.

size

public abstract int size()

Returns the number of features for this object.

Returns:

The number of features for this object.