gov.sandia.cognition.text.topic
Class LatentSemanticAnalysis.Transform

java.lang.Object
  gov.sandia.cognition.util.AbstractCloneableSerializable
      gov.sandia.cognition.text.topic.LatentSemanticAnalysis.Transform

All Implemented Interfaces:

Evaluator<Vectorizable,Vector>, VectorInputEvaluator<Vectorizable,Vector>, VectorOutputEvaluator<Vectorizable,Vector>, CloneableSerializable, Serializable, Cloneable

Enclosing class:

LatentSemanticAnalysis

public static class LatentSemanticAnalysis.Transform
extends AbstractCloneableSerializable
implements Evaluator<Vectorizable,Vector>, VectorInputEvaluator<Vectorizable,Vector>, VectorOutputEvaluator<Vectorizable,Vector>

The result from doing latent semantic analysis (LSA). It is a transform that can be applied as a dimensionality reduction.

See Also:

Serialized Form

Field Summary

protected Matrix	singularValues The diagonal matrix of singular values.
protected Matrix	termBasis The matrix of orthogonal term column vectors.
protected Matrix	transform The cached transform matrix.

Constructor Summary

LatentSemanticAnalysis.Transform(Matrix termBasis, Matrix singularValues)
Create a new Transform

Method Summary

Vector	evaluate(Vectorizable input) Evaluates the function on the given input and returns the output.
int	getInputDimensionality() Gets the expected dimensionality of the input vector to the evaluator, if it is known.
int	getOutputDimensionality() Gets the expected dimensionality of the output vector of the evaluator, if it is known.
int	getRank() Gets the rank of the LSA.
Matrix	getSingularValues() Gets the diagonal matrix of singular values.
Matrix	getTermBasis() Gets the matrix of orthogonal term column vectors.
Vector	getTermVector(int i) Gets the i-th orthogonal term vector that makes up the basis for the transform.
Matrix	getTransform() Gets the cached transform matrix.
protected void	setSingularValues(Matrix singularValues) Sets the diagonal matrix of singular values.
protected void	setTermBasis(Matrix termBasis) Sets the matrix of orthogonal term column vectors.
protected void	setTransform(Matrix transform) Gets the cached transform matrix.

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

termBasis

protected Matrix termBasis

The matrix of orthogonal term column vectors.

singularValues

protected Matrix singularValues

The diagonal matrix of singular values.

transform

protected Matrix transform

The cached transform matrix. It is the term basis times the singular values.

Constructor Detail

LatentSemanticAnalysis.Transform

public LatentSemanticAnalysis.Transform(Matrix termBasis,
                                        Matrix singularValues)

Create a new Transform

Parameters:

termBasis - The matrix of orthogonal term column vectors.

singularValues - The diagonal matrix of singular values.

Method Detail

evaluate

public Vector evaluate(Vectorizable input)

Description copied from interface: Evaluator

Evaluates the function on the given input and returns the output.

Specified by:

evaluate in interface Evaluator<Vectorizable,Vector>

Parameters:

input - The input to evaluate.

Returns:

The output produced by evaluating the input.

getInputDimensionality

public int getInputDimensionality()

Description copied from interface: VectorInputEvaluator

Gets the expected dimensionality of the input vector to the evaluator, if it is known. If it is not known, -1 is returned.

Specified by:

getInputDimensionality in interface VectorInputEvaluator<Vectorizable,Vector>

Returns:

The expected dimensionality of the input vector to the evaluator, or -1 if it is not known.

getOutputDimensionality

public int getOutputDimensionality()

Description copied from interface: VectorOutputEvaluator

Gets the expected dimensionality of the output vector of the evaluator, if it is known. If it is not known, -1 is returned.

Specified by:

getOutputDimensionality in interface VectorOutputEvaluator<Vectorizable,Vector>

Returns:

The expected dimensionality of the output vector of the evaluator, or -1 if it is not known.

getRank

public int getRank()

Gets the rank of the LSA. This is equivalent to the output dimensionality of the transform.

Returns:

The rank of the LSA.

getTermVector

public Vector getTermVector(int i)

Gets the i-th orthogonal term vector that makes up the basis for the transform.

Parameters:

i - An index. Must be between 0 (inclusive) and rank (exclusive).

Returns:

The i-th orthogonal term vector.

getTermBasis

public Matrix getTermBasis()

Gets the matrix of orthogonal term column vectors.

Returns:

The matrix of orthogonal term column vectors.

setTermBasis

protected void setTermBasis(Matrix termBasis)

Sets the matrix of orthogonal term column vectors.

Parameters:

termBasis - The matrix of orthogonal term column vectors.

getSingularValues

public Matrix getSingularValues()

Gets the diagonal matrix of singular values.

Returns:

The diagonal matrix of singular values.

setSingularValues

protected void setSingularValues(Matrix singularValues)

Sets the diagonal matrix of singular values.

Parameters:

singularValues - The diagonal matrix of singular values.

getTransform

public Matrix getTransform()

Gets the cached transform matrix. It is the term basis times the singular values.

Returns:

The cached transform matrix.

setTransform

protected void setTransform(Matrix transform)

Gets the cached transform matrix. It is the term basis times the singular values.

Parameters:

transform - The cached transform matrix.