PCAWhitening Class Reference

A simple PCAWhitening class. More...

Public Member Functions
	PCAWhitening (double eps=0.00005)
	A constructor to set the regularization parameter. More...
const arma::vec &	EigenValues () const
	Get the eigenvalues vector. More...
const arma::mat &	EigenVectors () const
	Get the eigenvector. More...
const double &	Epsilon () const
	Get the regularization parameter. More...
template < typename MatType >
void	Fit (const MatType &input)
	Function to fit features, to find out the min max and scale. More...
template < typename MatType >
void	InverseTransform (const MatType &input, MatType &output)
	Function to retrieve original dataset. More...
const arma::vec &	ItemMean () const
	Get the mean row vector. More...
template < typename Archive >
void	serialize (Archive &ar, const unsigned int)
template < typename MatType >
void	Transform (const MatType &input, MatType &output)
	Function for PCA whitening. More...

Detailed Description

A simple PCAWhitening class.

Whitens a matrix using the eigendecomposition of the covariance matrix. Whitening means the covariance matrix of the result is the identity matrix.

For whitening related formula and more info, check the link below. http://ufldl.stanford.edu/tutorial/unsupervised/PCAWhitening/

arma::mat input;
Load("train.csv", input);
arma::mat output;

// Fit the features.
PCAWhitening scale;
scale.Fit(input)

// Scale the features.
scale.Transform(input, output);

// Retransform the input.
scale.InverseTransform(output, input);

Definition at line 46 of file pca_whitening.hpp.

Constructor & Destructor Documentation

PCAWhitening()

PCAWhitening ( double  eps = 0.00005 )

inline

A constructor to set the regularization parameter.

Parameters

eps	Regularization parameter.

Definition at line 54 of file pca_whitening.hpp.

Member Function Documentation

EigenValues()

const arma::vec& EigenValues ( ) const

inline

Get the eigenvalues vector.

Definition at line 116 of file pca_whitening.hpp.

Referenced by ZCAWhitening::EigenValues(), and ZCAWhitening::InverseTransform().

EigenVectors()

const arma::mat& EigenVectors ( ) const

inline

Get the eigenvector.

Definition at line 118 of file pca_whitening.hpp.

Referenced by ZCAWhitening::EigenVectors(), ZCAWhitening::InverseTransform(), and ZCAWhitening::Transform().

Epsilon()

const double& Epsilon ( ) const

inline

Get the regularization parameter.

Definition at line 120 of file pca_whitening.hpp.

Referenced by ZCAWhitening::Epsilon().

Fit()

void Fit ( const MatType &  input )

inline

Function to fit features, to find out the min max and scale.

Parameters

input

Dataset to fit.

Definition at line 70 of file pca_whitening.hpp.

References mlpack::math::ColumnCovariance().

Referenced by ZCAWhitening::Fit().

InverseTransform()

void InverseTransform ( const MatType &  input, MatType &  output  )

inline

Function to retrieve original dataset.

Parameters

input	Scaled dataset.
output	Output matrix with original Dataset.

Definition at line 106 of file pca_whitening.hpp.

ItemMean()

const arma::vec& ItemMean ( ) const

inline

Get the mean row vector.

Definition at line 114 of file pca_whitening.hpp.

Referenced by ZCAWhitening::InverseTransform(), and ZCAWhitening::ItemMean().

serialize()

void serialize ( Archive &  ar, const unsigned  int  )

inline

Definition at line 123 of file pca_whitening.hpp.

Transform()

void Transform ( const MatType &  input, MatType &  output  )

inline

Function for PCA whitening.

Parameters

input	Dataset to scale features.
output	Output matrix with whitened features.

Definition at line 86 of file pca_whitening.hpp.

Referenced by ZCAWhitening::Transform().

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The documentation for this class was generated from the following file:

• /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.2.1/src/mlpack/core/data/scaler_methods/pca_whitening.hpp