lti::linearDiscriminantAnalysis< T >::parameters Class Reference

the parameters for the class linearDiscriminantAnalysis More...

#include <ltiLDA.h>

Inheritance diagram for lti::linearDiscriminantAnalysis< T >::parameters:

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Collaboration diagram for lti::linearDiscriminantAnalysis< T >::parameters:

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List of all members.

Public Member Functions
	parameters ()
	parameters (const parameters &other)
	~parameters ()
const char *	getTypeName () const
parameters &	copy (const parameters &other)
virtual functor::parameters *	clone () const
virtual bool	read (ioHandler &handler, const bool complete=true)
virtual bool	write (ioHandler &handler, const bool complete=true) const
Public Attributes
int	resultDim
bool	autoDim
bool	useSVD

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Detailed Description

template<class T>
class lti::linearDiscriminantAnalysis< T >::parameters

the parameters for the class linearDiscriminantAnalysis

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Constructor & Destructor Documentation

template<class T >

lti::linearDiscriminantAnalysis< T >::parameters::parameters

(

)

default constructor

Reimplemented from lti::linearAlgebraFunctor::parameters.

template<class T >

lti::linearDiscriminantAnalysis< T >::parameters::parameters

(

const parameters &

other

)

copy constructor

Parameters:

other

the parameters object to be copied

Reimplemented from lti::linearAlgebraFunctor::parameters.

template<class T >

lti::linearDiscriminantAnalysis< T >::parameters::~parameters

(

)

[virtual]

destructor

Reimplemented from lti::linearAlgebraFunctor::parameters.

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Member Function Documentation

template<class T >

virtual functor::parameters* lti::linearDiscriminantAnalysis< T >::parameters::clone

(

)

const [virtual]

returns a pointer to a clone of the parameters

Reimplemented from lti::linearAlgebraFunctor::parameters.

template<class T >

parameters& lti::linearDiscriminantAnalysis< T >::parameters::copy

(

const parameters &

other

)

copy the contents of a parameters object

Parameters:

other

the parameters object to be copied

Returns:

a reference to this parameters object

Reimplemented from lti::linearAlgebraFunctor::parameters.

template<class T >

const char* lti::linearDiscriminantAnalysis< T >::parameters::getTypeName

(

)

const [virtual]

returns name of this type

Reimplemented from lti::linearAlgebraFunctor::parameters.

template<class T >

virtual bool lti::linearDiscriminantAnalysis< T >::parameters::read	(	ioHandler &	handler,
		const bool	complete = true
	)			[virtual]

read the parametersfrom the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::linearAlgebraFunctor::parameters.

template<class T >

virtual bool lti::linearDiscriminantAnalysis< T >::parameters::write	(	ioHandler &	handler,
		const bool	complete = true
	)			const [virtual]

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::linearAlgebraFunctor::parameters.

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Member Data Documentation

template<class T >

bool lti::linearDiscriminantAnalysis< T >::parameters::autoDim

This flag determines, if the functor should determine a maximum allowable dimension itself.

"Maximum dimension" means that the dimension is equal to the number of eigenvalues of the covariance matrix which are larger than zero.

Default value: false

template<class T >

int lti::linearDiscriminantAnalysis< T >::parameters::resultDim

This is the dimension of the reduced vectors.

template<class T >

bool lti::linearDiscriminantAnalysis< T >::parameters::useSVD

If true, singular value decomposition instead of LU decomposition is used for inverting the Sw (within-class scatter) matrix.

This is much safer than the original method, since it always computes a meaningful result: for singular matrices, it computes the closest approximation.

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

• ltiLDA.h