cv::LDA Class Reference

Linear Discriminant Analysis. More...

#include "core.hpp"

Public Member Functions
	LDA (int num_components=0)
	constructor Initializes a LDA with num_components (default 0). More...
	LDA (InputArrayOfArrays src, InputArray labels, int num_components=0)
	~LDA ()
void	compute (InputArrayOfArrays src, InputArray labels)
Mat	eigenvalues () const
Mat	eigenvectors () const
void	load (const String &filename)
void	load (const FileStorage &node)
Mat	project (InputArray src)
Mat	reconstruct (InputArray src)
void	save (const String &filename) const
void	save (FileStorage &fs) const

Static Public Member Functions
static Mat	subspaceProject (InputArray W, InputArray mean, InputArray src)
static Mat	subspaceReconstruct (InputArray W, InputArray mean, InputArray src)

Protected Member Functions
void	lda (InputArrayOfArrays src, InputArray labels)

Protected Attributes
bool	_dataAsRow
Mat	_eigenvalues
Mat	_eigenvectors
int	_num_components

Detailed Description

Linear Discriminant Analysis.

Todo:

document this class

Constructor & Destructor Documentation

LDA() [1/2]

cv::LDA::LDA ( int  num_components = 0 )

explicit

constructor Initializes a LDA with num_components (default 0).

LDA() [2/2]

cv::LDA::LDA	(	InputArrayOfArrays	src,
		InputArray	labels,
		int	num_components = 0
	)

Initializes and performs a Discriminant Analysis with Fisher's Optimization Criterion on given data in src and corresponding labels in labels. If 0 (or less) number of components are given, they are automatically determined for given data in computation.

~LDA()

cv::LDA::~LDA

(

)

destructor

Member Function Documentation

compute()

void cv::LDA::compute	(	InputArrayOfArrays	src,
		InputArray	labels
	)

Compute the discriminants for data in src (row aligned) and labels.

eigenvalues()

Mat cv::LDA::eigenvalues ( ) const

inline

Returns the eigenvalues of this LDA.

eigenvectors()

Mat cv::LDA::eigenvectors ( ) const

inline

Returns the eigenvectors of this LDA.

lda()

void cv::LDA::lda ( InputArrayOfArrays  src, InputArray  labels  )

protected

load() [1/2]

void cv::LDA::load

(

const String &

filename

)

Deserializes this object from a given filename.

load() [2/2]

void cv::LDA::load

(

const FileStorage &

node

)

Deserializes this object from a given cv::FileStorage.

project()

Mat cv::LDA::project

(

InputArray

src

)

Projects samples into the LDA subspace. src may be one or more row aligned samples.

reconstruct()

Mat cv::LDA::reconstruct

(

InputArray

src

)

Reconstructs projections from the LDA subspace. src may be one or more row aligned projections.

save() [1/2]

void cv::LDA::save

(

const String &

filename

)

const

Serializes this object to a given filename.

save() [2/2]

void cv::LDA::save

(

FileStorage &

fs

)

const

Serializes this object to a given cv::FileStorage.

subspaceProject()

static Mat cv::LDA::subspaceProject ( InputArray  W, InputArray  mean, InputArray  src  )

static

subspaceReconstruct()

static Mat cv::LDA::subspaceReconstruct ( InputArray  W, InputArray  mean, InputArray  src  )

static

Member Data Documentation

_dataAsRow

bool cv::LDA::_dataAsRow

protected

_eigenvalues

Mat cv::LDA::_eigenvalues

protected

_eigenvectors

Mat cv::LDA::_eigenvectors

protected

_num_components

int cv::LDA::_num_components

protected

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

• core/include/opencv2/core.hpp