be.ac.ulg.montefiore.run.jahmm
Interface Centroid<O>

All Known Implementing Classes:

CentroidObservationInteger, CentroidObservationReal, CentroidObservationVector

public interface Centroid<O>

The centroid (basically, the mean) of a cluster. Used by the k-means algorithm.

Method Summary

double	distance(O e) Returns the distance from this centroid to a given element.
void	reevaluateAdd(O e, java.util.List<? extends O> v) Reevalue the value of this centroid, knowing that it currently is the centroid of the observations composing v and that we want it to be the centroid of v plus the value of the observation e.
void	reevaluateRemove(O e, java.util.List<? extends O> v) Reevalue the value of this centroid, knowing that it currently is the centroid of the observations composing v and that we want it to be the centroid of v minus the value of the observation e.

Method Detail

reevaluateAdd

void reevaluateAdd(O e,
                   java.util.List<? extends O> v)

Reevalue the value of this centroid, knowing that it currently is the centroid of the observations composing v and that we want it to be the centroid of v plus the value of the observation e.

Parameters:

e - An observation that must be involved in the computation of the new value of this centroid.

v - The set of observations that gave the current value of this centroid.

reevaluateRemove

void reevaluateRemove(O e,
                      java.util.List<? extends O> v)

Reevalue the value of this centroid, knowing that it currently is the centroid of the observations composing v and that we want it to be the centroid of v minus the value of the observation e.

Parameters:

e - An observation that must not be involved in the computation of the new value of this centroid.

v - The set of observations (which holds o) that gave the current value of this centroid.

distance

double distance(O e)

Returns the distance from this centroid to a given element.

Parameters:

e - The element.

Returns:

The distance to the centroid.