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java.lang.Objectshared.stat.ml.AbstractGMModel
shared.stat.ml.GMModel
public class GMModel

An implementation of AbstractGMModel using EM updates on GMM's with diagonal covariances. Inspired by Lawrence Saul's EM code.
| Constructor Summary | |
|---|---|
GMModel()
Default constructor. |
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| Method Summary | |
|---|---|
RealArray |
computeLogWeightedDensities(GMComponents gmc,
RealArray points)
Computes the log of the weighted densities. |
GMComponents |
initialize(RealArray input,
int ncomps,
double regularization)
Initializes the mixture components. |
void |
update(GMComponents gmc,
RealArray posterior,
RealArray points,
double regularization)
Performs the update rule. |
| Methods inherited from class shared.stat.ml.AbstractGMModel |
|---|
computePosterior, train |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public GMModel()
| Method Detail |
|---|
public GMComponents initialize(RealArray input,
int ncomps,
double regularization)
AbstractGMModel
initialize in class AbstractGMModelinput - the input.ncomps - the number of components.regularization - the regularization hint.
public void update(GMComponents gmc,
RealArray posterior,
RealArray points,
double regularization)
AbstractGMModel
update in class AbstractGMModelgmc - the mixture components.posterior - the posterior distribution p(components | points).points - the input.regularization - the regularization hint.
public RealArray computeLogWeightedDensities(GMComponents gmc,
RealArray points)
AbstractGMModel
computeLogWeightedDensities in class AbstractGMModelgmc - the mixture components.points - the input.
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