public class GaussianContextRecognizer extends AbstractCloneableSerializable implements VectorFunction, VectorInputEvaluator<Vector,Vector>, VectorOutputEvaluator<Vector,Vector>
Modifier and Type | Class and Description |
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static class |
GaussianContextRecognizer.Learner
Creates a GaussianContextRecognizer from a Dataset[Vector] using
a BatchClusterer
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Constructor and Description |
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GaussianContextRecognizer()
Creates a new instance of GaussianContextRecognizer
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GaussianContextRecognizer(java.util.Collection<GaussianCluster> clusters)
Creates a new instance of GaussianContextRecognizer
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GaussianContextRecognizer(GaussianContextRecognizer other)
Copy constructor
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GaussianContextRecognizer(MixtureOfGaussians.PDF gaussianMixture)
Creates a new instance of GaussianContextRecognizer
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Modifier and Type | Method and Description |
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GaussianContextRecognizer |
clone()
This makes public the clone method on the
Object class and
removes the exception that it throws. |
void |
consumeClusters(java.util.Collection<GaussianCluster> clusters)
Uses the given clusters to populate the internal clusters of this
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Vector |
evaluate(Vector input)
Evaluates the function on the given input and returns the output.
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MixtureOfGaussians.PDF |
getGaussianMixture()
Getter for gaussianMixture
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int |
getInputDimensionality()
Gets the expected dimensionality of the input vector to the evaluator,
if it is known.
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int |
getOutputDimensionality()
Gets the expected dimensionality of the output vector of the evaluator,
if it is known.
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void |
setGaussianMixture(MixtureOfGaussians.PDF gaussianMixture)
Setter for gaussianMixture
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public GaussianContextRecognizer()
public GaussianContextRecognizer(MixtureOfGaussians.PDF gaussianMixture)
gaussianMixture
- Underlying MixtureOfGaussians that computes context probabilitiespublic GaussianContextRecognizer(java.util.Collection<GaussianCluster> clusters)
clusters
- public GaussianContextRecognizer(GaussianContextRecognizer other)
other
- GaussianContextRecognizer to clonepublic GaussianContextRecognizer 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 Vector evaluate(Vector input)
Evaluator
public void consumeClusters(java.util.Collection<GaussianCluster> clusters)
clusters
- Clusters from which to create the data for thispublic MixtureOfGaussians.PDF getGaussianMixture()
public void setGaussianMixture(MixtureOfGaussians.PDF gaussianMixture)
gaussianMixture
- Underlying MixtureOfGaussians that computes context probabilitiespublic int getInputDimensionality()
VectorInputEvaluator
getInputDimensionality
in interface VectorInputEvaluator<Vector,Vector>
public int getOutputDimensionality()
VectorOutputEvaluator
getOutputDimensionality
in interface VectorOutputEvaluator<Vector,Vector>