public static class DirichletProcessMixtureModel.MultivariateMeanUpdater extends AbstractCloneableSerializable implements DirichletProcessMixtureModel.Updater<Vector>
Modifier and Type | Field and Description |
---|---|
protected MultivariateGaussianMeanBayesianEstimator |
estimator
Bayesian estimator for the parameters
|
Constructor and Description |
---|
MultivariateMeanUpdater()
Default constructor
|
MultivariateMeanUpdater(int dimensionality)
Creates a new instance of MeanCovarianceUpdater
|
MultivariateMeanUpdater(MultivariateGaussianMeanBayesianEstimator estimator)
Creates a new instance of MeanUpdater
|
Modifier and Type | Method and Description |
---|---|
DirichletProcessMixtureModel.MultivariateMeanUpdater |
clone()
This makes public the clone method on the
Object class and
removes the exception that it throws. |
MultivariateGaussian.PDF |
createClusterPosterior(java.lang.Iterable<? extends Vector> values,
java.util.Random random)
Updates the cluster from the values assigned to it
|
MultivariateGaussian.PDF |
createPriorPredictive(java.lang.Iterable<? extends Vector> data)
Creates the prior predictive distribution from the data.
|
protected MultivariateGaussianMeanBayesianEstimator estimator
public MultivariateMeanUpdater()
public MultivariateMeanUpdater(int dimensionality)
dimensionality
- Dimensionality of the Vectorspublic MultivariateMeanUpdater(MultivariateGaussianMeanBayesianEstimator estimator)
estimator
- Bayesian estimator for the parameterspublic DirichletProcessMixtureModel.MultivariateMeanUpdater clone()
AbstractCloneableSerializable
Object
class and
removes the exception that it throws. Its default behavior is to
automatically create a clone of the exact type of object that the
clone is called on and to copy all primitives but to keep all references,
which means it is a shallow copy.
Extensions of this class may want to override this method (but call
super.clone()
to implement a "smart copy". That is, to target
the most common use case for creating a copy of the object. Because of
the default behavior being a shallow copy, extending classes only need
to handle fields that need to have a deeper copy (or those that need to
be reset). Some of the methods in ObjectUtil
may be helpful in
implementing a custom clone method.
Note: The contract of this method is that you must use
super.clone()
as the basis for your implementation.clone
in interface CloneableSerializable
clone
in class AbstractCloneableSerializable
public MultivariateGaussian.PDF createPriorPredictive(java.lang.Iterable<? extends Vector> data)
DirichletProcessMixtureModel.Updater
createPriorPredictive
in interface DirichletProcessMixtureModel.Updater<Vector>
data
- Data from which to create the prior predictivepublic MultivariateGaussian.PDF createClusterPosterior(java.lang.Iterable<? extends Vector> values, java.util.Random random)
DirichletProcessMixtureModel.Updater
createClusterPosterior
in interface DirichletProcessMixtureModel.Updater<Vector>
values
- Values assigned to the clusterrandom
- Random number generator