public static class MultivariateGaussian.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements DistributionWeightedEstimator<Vector,MultivariateGaussian.PDF>
Modifier and Type | Field and Description |
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static double |
DEFAULT_COVARIANCE
Default covariance used in estimation, 1.0E-5.
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Constructor and Description |
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WeightedMaximumLikelihoodEstimator()
Default constructor.
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WeightedMaximumLikelihoodEstimator(double defaultCovariance)
Creates a new instance of WeightedMaximumLikelihoodEstimator
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Modifier and Type | Method and Description |
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MultivariateGaussian.PDF |
learn(java.util.Collection<? extends WeightedValue<? extends Vector>> data)
Computes the Gaussian that estimates the maximum likelihood of
generating the given set of weighted samples.
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static MultivariateGaussian.PDF |
learn(java.util.Collection<? extends WeightedValue<? extends Vector>> data,
double defaultCovariance)
Computes the Gaussian that estimates the maximum likelihood of
generating the given set of weighted samples.
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clone
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clone
public static final double DEFAULT_COVARIANCE
public WeightedMaximumLikelihoodEstimator()
public WeightedMaximumLikelihoodEstimator(double defaultCovariance)
defaultCovariance
- Amount to add to the diagonal of the
covariance matrixpublic MultivariateGaussian.PDF learn(java.util.Collection<? extends WeightedValue<? extends Vector>> data)
learn
in interface BatchLearner<java.util.Collection<? extends WeightedValue<? extends Vector>>,MultivariateGaussian.PDF>
data
- The weighted samples to calculate the Gaussian from
throws IllegalArgumentException if samples has 1 or fewer samples.public static MultivariateGaussian.PDF learn(java.util.Collection<? extends WeightedValue<? extends Vector>> data, double defaultCovariance)
defaultCovariance
- Amount to add to the diagonal of the
covariance matrixdata
- The weighted samples to calculate the Gaussian from
throws IllegalArgumentException if samples has 1 or fewer samples.