Class to perform linear discriminant analysis. More...

#include <mbl_lda.h>

Public Member Functions
	mbl_lda ()
	Dflt ctor.
virtual	~mbl_lda ()
	Destructor.
bool	operator== (const mbl_lda &that) const
	Comparison.
int	classify (const vnl_vector< double > &x) const
	Classify a new data point.
void	build (const vnl_vector< double > v, const int label, int n)
	Perform LDA on data.
void	build (const vnl_vector< double > *v, const vcl_vector< int > &label)
	Perform LDA on data.
void	build (const vnl_vector< double > *v, const vcl_vector< int > &label, const vnl_matrix< double > &wS)
	Perform LDA on data.
void	build (const vcl_vector< vnl_vector< double > > &v, const vcl_vector< int > &label)
	Perform LDA on data.
void	build (const vcl_vector< vnl_vector< double > > &v, const vcl_vector< int > &label, const vnl_matrix< double > &wS)
	Perform LDA on data.
void	build (const vnl_matrix< double > &M, const vcl_vector< int > &label)
	Perform LDA on data.
void	build (const vnl_matrix< double > &M, const vcl_vector< int > &label, const vnl_matrix< double > &wS)
	Perform LDA on data.
int	n_classes () const
	Number of classes.
int	n_samples (int i) const
	Number of examples of each class.
const vnl_vector< double > &	class_mean (int i) const
	Mean vector for i'th class in original space.
const vnl_vector< double > &	d_class_mean (int i) const
	Mean vector for i'th class in discriminant space.
const vnl_vector< double > &	mean_class_mean () const
	Mean of means for each class.
const vnl_matrix< double > &	within_covar () const
	Within class covariance matrix.
const vnl_matrix< double > &	between_covar () const
	Between class covariance matrix.
const vnl_matrix< double > &	basis () const
	Basis for discriminant space.
const vnl_vector< double > &	basis_e_vals () const
	Eigenvalues associated with each basis vector.
void	x_to_d (vnl_vector< double > &d, const vnl_vector< double > &x) const
	Project x into discriminant space.
void	d_to_x (vnl_vector< double > &x, const vnl_vector< double > &d) const
	Project d from discriminant space into original space.
int	nDistinctIDs (const int *id, const int n)
	find out how many id in the label vector.
short	version_no () const
	Version number for I/O.
virtual vcl_string	is_a () const
	Name of the class.
virtual bool	is_class (vcl_string const &s) const
	True if this is (or is derived from) class named s.
virtual void	print_summary (vcl_ostream &os) const
	Print class to os.
virtual void	b_write (vsl_b_ostream &bfs) const
	Save class to binary file stream.
virtual void	b_read (vsl_b_istream &bfs)
	Load class from binary file stream.
Private Member Functions
void	updateCovar (vnl_matrix< double > &S, const vnl_vector< double > &v)
void	build (const vnl_vector< double > v, const int label, int n, const vnl_matrix< double > &wS, bool compute_wS)
	Perform LDA on data.
Private Attributes
vcl_vector< vnl_vector< double > >	mean_
vcl_vector< vnl_vector< double > >	d_mean_
vnl_vector< double >	mean_class_mean_
vcl_vector< int >	n_samples_
vnl_matrix< double >	withinS_
vnl_matrix< double >	betweenS_
vnl_matrix< double >	basis_
vnl_vector< double >	evals_
vnl_vector< double >	d_m_mean_

Detailed Description

Class to perform linear discriminant analysis.

Definition at line 23 of file mbl_lda.h.

Constructor & Destructor Documentation

mbl_lda::mbl_lda ( )

Dflt ctor.

Definition at line 40 of file mbl_lda.cxx.

mbl_lda::~mbl_lda ( ) [virtual]

Destructor.

Definition at line 46 of file mbl_lda.cxx.

Member Function Documentation

void mbl_lda::b_read ( vsl_b_istream & bfs ) [virtual]

Load class from binary file stream.

Definition at line 478 of file mbl_lda.cxx.

void mbl_lda::b_write ( vsl_b_ostream & bfs ) const [virtual]

Save class to binary file stream.

Definition at line 462 of file mbl_lda.cxx.

const vnl_matrix<double>& mbl_lda::basis ( ) const [inline]

Basis for discriminant space.

Definition at line 165 of file mbl_lda.h.

const vnl_vector<double>& mbl_lda::basis_e_vals ( ) const [inline]

Eigenvalues associated with each basis vector.

Definition at line 168 of file mbl_lda.h.

const vnl_matrix<double>& mbl_lda::between_covar ( ) const [inline]

Between class covariance matrix.

Definition at line 162 of file mbl_lda.h.

void mbl_lda::build	(	const vnl_vector< double > *	v,
		const int *	label,
		int	n,
		const vnl_matrix< double > &	wS,
		bool	compute_wS
	)		`[private]`

Perform LDA on data.

Classes must be labeled from 0..n-1

Parameters:

label	Array [0..n-1] of integer indices. label[i] gives class of v[i]
n	Size of label and of v
v	Set of vectors [0..n-1]
wS	Within class covariance to use if compute_wS false
compute_wS	This boolean parameter determines whether to use wS
label	Array [0..n-1] of integers indices
v	Set of vectors [0..n-1]

label[i] gives class of v[i] Classes must be labeled from 0 to m-1

Definition at line 130 of file mbl_lda.cxx.

void mbl_lda::build	(	const vnl_vector< double > *	v,
		const int *	label,
		int	n
	)

Perform LDA on data.

Parameters:

n	Number of examples
label	integer indices
v	Set of vectors [0..n-1]

label[i] gives class of v[i]
If label[i]<0 the class is assumed to be unknown and example i is ignored
Classes must be labeled from 0..n-1

Definition at line 329 of file mbl_lda.cxx.

void mbl_lda::build	(	const vnl_vector< double > *	v,
		const vcl_vector< int > &	label
	)

Perform LDA on data.

Parameters:

label	Array [0..n-1] of integers indices
v	Set of vectors [0..n-1]

label[i] gives class of v[i]
If label[i]<0 the class is assumed to be unknown and example i is ignored
Classes must be labeled from 0..n-1

Definition at line 336 of file mbl_lda.cxx.

void mbl_lda::build	(	const vnl_vector< double > *	v,
		const vcl_vector< int > &	label,
		const vnl_matrix< double > &	wS
	)

Perform LDA on data.

Parameters:

label	Array [0..n-1] of integers indices
v	Set of vectors [0..n-1]
wS	Within class covariance to use

label[i] gives class of v[i]
If label[i]<0 the class is assumed to be unknown and example i is ignored
Classes must be labeled from 0..n-1

Definition at line 343 of file mbl_lda.cxx.

void mbl_lda::build	(	const vcl_vector< vnl_vector< double > > &	v,
		const vcl_vector< int > &	label
	)

Perform LDA on data.

Parameters:

label	Array [0..n-1] of integers indices
v	Set of vectors [0..n-1]

label[i] gives class of v[i]
If label[i]<0 the class is assumed to be unknown and example i is ignored
Classes must be labeled from 0..n-1

Definition at line 351 of file mbl_lda.cxx.

void mbl_lda::build	(	const vcl_vector< vnl_vector< double > > &	v,
		const vcl_vector< int > &	label,
		const vnl_matrix< double > &	wS
	)

Perform LDA on data.

Parameters:

label	Array [0..n-1] of integers indices
v	Set of vectors [0..n-1]
wS	Within class covariance to use

label[i] gives class of v[i]
Classes must be labeled from 0..n-1
If label[i]<0 the class is assumed to be unknown and example i is ignored

Definition at line 359 of file mbl_lda.cxx.

void mbl_lda::build	(	const vnl_matrix< double > &	M,
		const vcl_vector< int > &	label
	)

Perform LDA on data.

Columns of M form example vectors
i'th column belongs to class label(i)
Note: label([1..n]) not label([0..n-1])
If label[i]<0 the class is assumed to be unknown and example i is ignored
Note also that this is inefficient - it converts the matrix to an array and calls build(v,label)

Columns of M form example vectors i'th column belongs to class label[i] Note: label([1..n]) not label([0..n-1])

Definition at line 371 of file mbl_lda.cxx.

void mbl_lda::build	(	const vnl_matrix< double > &	M,
		const vcl_vector< int > &	label,
		const vnl_matrix< double > &	wS
	)

Perform LDA on data.

Columns of M form example vectors
i'th column belongs to class label(i)
Note: label([1..n]) not label([0..n-1])
Note also that this is inefficient - it converts the matrix to an array and calls build(v,label)
If label[i]<0 the class is assumed to be unknown and example i is ignored
Parameters:

M The columns of this matrix for the example vectors

label The vector of class labels corresponding to these examples

wS Within class covariance to use

Columns of M form example vectors i'th column belongs to class label[i] Note: label([1..n]) not label([0..n-1])

Definition at line 389 of file mbl_lda.cxx.

const vnl_vector<double>& mbl_lda::class_mean ( int i ) const [inline]

Mean vector for i'th class in original space.

Definition at line 150 of file mbl_lda.h.

int mbl_lda::classify ( const vnl_vector< double > & x ) const

Classify a new data point.

projects into discriminant space and picks closest mean class vector

Projects into discriminant space and picks closest mean class vector

Definition at line 54 of file mbl_lda.cxx.

const vnl_vector<double>& mbl_lda::d_class_mean ( int i ) const [inline]

Mean vector for i'th class in discriminant space.

Definition at line 153 of file mbl_lda.h.

void mbl_lda::d_to_x	(	vnl_vector< double > &	x,
		const vnl_vector< double > &	d
	)		const

Project d from discriminant space into original space.

Definition at line 415 of file mbl_lda.cxx.

vcl_string mbl_lda::is_a ( ) const [virtual]

Name of the class.

Definition at line 430 of file mbl_lda.cxx.

bool mbl_lda::is_class ( vcl_string const & s ) const [virtual]

True if this is (or is derived from) class named s.

Definition at line 435 of file mbl_lda.cxx.

const vnl_vector<double>& mbl_lda::mean_class_mean ( ) const [inline]

Mean of means for each class.

Definition at line 156 of file mbl_lda.h.

int mbl_lda::n_classes ( ) const [inline]

Number of classes.

Definition at line 144 of file mbl_lda.h.

int mbl_lda::n_samples ( int i ) const [inline]

Number of examples of each class.

Definition at line 147 of file mbl_lda.h.

int mbl_lda::nDistinctIDs	(	const int *	id,
		const int	n
	)

find out how many id in the label vector.

Definition at line 110 of file mbl_lda.cxx.

bool mbl_lda::operator== ( const mbl_lda & that ) const

Comparison.

Definition at line 72 of file mbl_lda.cxx.

void mbl_lda::print_summary ( vcl_ostream & os ) const [virtual]

Print class to os.

Definition at line 442 of file mbl_lda.cxx.

void mbl_lda::updateCovar	(	vnl_matrix< double > &	S,
		const vnl_vector< double > &	v
	)		`[private]`

Definition at line 87 of file mbl_lda.cxx.

short mbl_lda::version_no ( ) const

Version number for I/O.

Definition at line 423 of file mbl_lda.cxx.

const vnl_matrix<double>& mbl_lda::within_covar ( ) const [inline]

Within class covariance matrix.

Definition at line 159 of file mbl_lda.h.

void mbl_lda::x_to_d	(	vnl_vector< double > &	d,
		const vnl_vector< double > &	x
	)		const

Project x into discriminant space.

Definition at line 406 of file mbl_lda.cxx.

Member Data Documentation

vnl_matrix<double> mbl_lda::basis_ [private]

Definition at line 33 of file mbl_lda.h.

vnl_matrix<double> mbl_lda::betweenS_ [private]

Definition at line 32 of file mbl_lda.h.

vnl_vector<double> mbl_lda::d_m_mean_ [private]

Definition at line 35 of file mbl_lda.h.

vcl_vector<vnl_vector<double> > mbl_lda::d_mean_ [private]

Definition at line 28 of file mbl_lda.h.

vnl_vector<double> mbl_lda::evals_ [private]

Definition at line 34 of file mbl_lda.h.

vcl_vector<vnl_vector<double> > mbl_lda::mean_ [private]

Definition at line 27 of file mbl_lda.h.

vnl_vector<double> mbl_lda::mean_class_mean_ [private]

Definition at line 29 of file mbl_lda.h.

vcl_vector<int> mbl_lda::n_samples_ [private]

Definition at line 30 of file mbl_lda.h.

vnl_matrix<double> mbl_lda::withinS_ [private]

Definition at line 31 of file mbl_lda.h.

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

contrib/mul/mbl/mbl_lda.h
contrib/mul/mbl/mbl_lda.cxx

M	The columns of this matrix for the example vectors
label	The vector of class labels corresponding to these examples
wS	Within class covariance to use

Public Member Functions

Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation