gov.sandia.cognition.learning.algorithm.pca
Class AbstractPrincipalComponentsAnalysis

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis
All Implemented Interfaces:
BatchLearner<Collection<Vector>,PrincipalComponentsAnalysisFunction>, PrincipalComponentsAnalysis, CloneableSerializable, Serializable, Cloneable
Direct Known Subclasses:
ThinSingularValueDecomposition

@CodeReview(reviewer="Kevin R. Dixon",
            date="2008-07-23",
            changesNeeded=false,
            comments={"Minor change to javadoc.","Looks fine."})
public abstract class AbstractPrincipalComponentsAnalysis
extends AbstractCloneableSerializable
implements PrincipalComponentsAnalysis

Abstract implementation of PCA.

Since:
2.0
Author:
Kevin R. Dixon
See Also:
Serialized Form

Constructor Summary
AbstractPrincipalComponentsAnalysis(int numComponents, PrincipalComponentsAnalysisFunction result)
          Creates a new instance of AbstractPrincipalComponentsAnalysis
 
Method Summary
 AbstractPrincipalComponentsAnalysis clone()
          This makes public the clone method on the Object class and removes the exception that it throws.
 int getNumComponents()
          Gets the number of components used in the PCA dimension reduction.
 PrincipalComponentsAnalysisFunction getResult()
          Gets the VectorFunction that maps from the input space to the reduced output space of "getNumComponents" dimensions.
 void setNumComponents(int numComponents)
          Setter for numComponents
protected  void setResult(PrincipalComponentsAnalysisFunction result)
          Setter for result
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner
learn
 

Constructor Detail

AbstractPrincipalComponentsAnalysis

public AbstractPrincipalComponentsAnalysis(int numComponents,
                                           PrincipalComponentsAnalysisFunction result)
Creates a new instance of AbstractPrincipalComponentsAnalysis

Parameters:
numComponents - Number of components to extract from the data, must be greater than zero
result - Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.
Method Detail

clone

public AbstractPrincipalComponentsAnalysis clone()
Description copied from class: AbstractCloneableSerializable
This makes public the clone method on the 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.

Specified by:
clone in interface CloneableSerializable
Overrides:
clone in class AbstractCloneableSerializable
Returns:
A clone of this object.

getNumComponents

public int getNumComponents()
Description copied from interface: PrincipalComponentsAnalysis
Gets the number of components used in the PCA dimension reduction.

Specified by:
getNumComponents in interface PrincipalComponentsAnalysis
Returns:
Number of components used in the PCA dimension reduction

setNumComponents

public void setNumComponents(int numComponents)
Setter for numComponents

Parameters:
numComponents - Number of components to extract from the data, must be greater than zero

getResult

public PrincipalComponentsAnalysisFunction getResult()
Description copied from interface: PrincipalComponentsAnalysis
Gets the VectorFunction that maps from the input space to the reduced output space of "getNumComponents" dimensions.

Specified by:
getResult in interface PrincipalComponentsAnalysis
Returns:
PCA function that reduces the dimensionality of the input space to a (hopefully) simpler and smaller output space

setResult

protected void setResult(PrincipalComponentsAnalysisFunction result)
Setter for result

Parameters:
result - Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.