org.openimaj.math.matrix.algorithm.pca

Class CovarPrincipalComponentAnalysis

java.lang.Object

org.openimaj.math.matrix.algorithm.pca.PrincipalComponentAnalysis

org.openimaj.math.matrix.algorithm.pca.CovarPrincipalComponentAnalysis

public class CovarPrincipalComponentAnalysis
extends PrincipalComponentAnalysis

Naive Principle Component Analysis performed by directly calculating the covariance matrix and then performing an Eigen decomposition. This implementation should not be used in general as it is expensive. The SvdPrincipalComponentAnalysis and ThinSvdPrincipalComponentAnalysis implementations are much faster and more efficient.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Nested Class Summary

Nested classes/interfaces inherited from class org.openimaj.math.matrix.algorithm.pca.PrincipalComponentAnalysis

PrincipalComponentAnalysis.ComponentSelector, PrincipalComponentAnalysis.EnergyThresholdComponentSelector, PrincipalComponentAnalysis.NumberComponentSelector, PrincipalComponentAnalysis.PercentageEnergyComponentSelector

Field Summary

Fields inherited from class org.openimaj.math.matrix.algorithm.pca.PrincipalComponentAnalysis

basis, eigenvalues, mean

Constructor Summary

Constructors

Constructor and Description
CovarPrincipalComponentAnalysis() Construct a CovarPrincipalComponentAnalysis that will extract all the eigenvectors.
CovarPrincipalComponentAnalysis(int ndims) Construct a CovarPrincipalComponentAnalysis that will extract the n best eigenvectors.

Method Summary

Modifier and Type	Method and Description
protected void	learnBasisNorm(Jama.Matrix m) Learn the PCA basis from the centered data provided.

Methods inherited from class org.openimaj.math.matrix.algorithm.pca.PrincipalComponentAnalysis

buildNormalisedDataMatrix, generate, getBasis, getCumulativeEnergies, getCumulativeEnergy, getEigenValue, getEigenValues, getEigenVectors, getMean, getPrincipalComponent, getStandardDeviations, getStandardDeviations, learnBasis, learnBasis, learnBasis, project, project, selectSubset, selectSubset, selectSubsetEnergyThreshold, selectSubsetPercentageEnergy, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

CovarPrincipalComponentAnalysis

public CovarPrincipalComponentAnalysis()

Construct a CovarPrincipalComponentAnalysis that will extract all the eigenvectors.

CovarPrincipalComponentAnalysis

public CovarPrincipalComponentAnalysis(int ndims)

Construct a CovarPrincipalComponentAnalysis that will extract the n best eigenvectors.

Parameters:

ndims - the number of eigenvectors to select.

Method Detail

learnBasisNorm

protected void learnBasisNorm(Jama.Matrix m)

Description copied from class: PrincipalComponentAnalysis

Learn the PCA basis from the centered data provided. Each row corresponds to an observation with the number of dimensions equal to the number of columns.

Specified by:

learnBasisNorm in class PrincipalComponentAnalysis