Example usage for org.apache.commons.math3.distribution.fitting MultivariateNormalMixtureExpectationMaximization getLogLikelihood

Introduction

In this page you can find the example usage for org.apache.commons.math3.distribution.fitting MultivariateNormalMixtureExpectationMaximization getLogLikelihood.

Prototype

public double getLogLikelihood() 

Source Link

Document

Gets the log likelihood of the data under the fitted model.

Usage

From source file:sly.speakrecognizer.test.math.MultivariateNormalMixtureExpectationMaximizationFitterTest.java

@Test
public void testFit() {
    // Test that the loglikelihood, weights, and models are determined and
    // fitted correctly
    double[][] data = getTestSamples();
    double correctLogLikelihood = -4.292431006791994;
    double[] correctWeights = new double[] { 0.2962324189652912, 0.7037675810347089 };
    MultivariateNormalDistribution[] correctMVNs = new MultivariateNormalDistribution[2];
    correctMVNs[0] = new MultivariateNormalDistribution(
            new double[] { -1.4213112715121132, 1.6924690505757753 }, new double[][] {
                    { 1.739356907285747, -0.5867644251487614 }, { -0.5867644251487614, 1.0232932029324642 } });

    correctMVNs[1] = new MultivariateNormalDistribution(new double[] { 4.213612224374709, 7.975621325853645 },
            new double[][] { { 4.245384898007161, 2.5797798966382155 },
                    { 2.5797798966382155, 3.9200272522448367 } });
    //=========================================
    MultivariateNormalMixtureExpectationMaximization fitter = new MultivariateNormalMixtureExpectationMaximization(
            data);/*ww  w . j  ava  2s. c  o m*/
    MixtureMultivariateNormalDistribution initialMix = MultivariateNormalMixtureExpectationMaximization
            .estimate(data, 2);
    fitter.fit(initialMix);
    MixtureMultivariateNormalDistribution fittedMix = fitter.getFittedModel();
    printMMND(fittedMix);
    List<Pair<Double, MultivariateNormalDistribution>> components = fittedMix.getComponents();

    Assert.assertEquals(correctLogLikelihood, fitter.getLogLikelihood(), Math.ulp(1d));

    int i = 0;
    for (Pair<Double, MultivariateNormalDistribution> component : components) {
        double weight = component.getFirst();
        MultivariateNormalDistribution mvn = component.getSecond();
        Assert.assertEquals(correctWeights[i], weight, Math.ulp(1d));
        assertMultivariateNormalDistribution(correctMVNs[i], mvn, 0);
        i++;
    }
}

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