PLearn::KPCATangentLearner Class Reference

#include <KPCATangentLearner.h>

Inheritance diagram for PLearn::KPCATangentLearner:

[legend]Collaboration diagram for PLearn::KPCATangentLearner:

[legend]List of all members.


Public Member Functions
	KPCATangentLearner ()
	Default constructor.
virtual void	build ()
	Simply calls inherited::build() then build_().
virtual void	makeDeepCopyFromShallowCopy (map< const void , void > &copies)
	Transforms a shallow copy into a deep copy.
	PLEARN_DECLARE_OBJECT (KPCATangentLearner)
virtual int	outputsize () const
	Returns the size of this learner's output, (which typically may depend on its inputsize(), targetsize() and set options).
virtual void	forget ()
	(Re-)initializes the PLearner in its fresh state (that state may depend on the 'seed' option) And sets 'stage' back to 0 (this is the stage of a fresh learner!).
virtual void	train ()
	The role of the train method is to bring the learner up to stage==nstages, updating the train_stats collector with training costs measured on-line in the process.
virtual void	computeOutput (const Vec &input, Vec &output) const
	Computes the output from the input.
virtual void	computeCostsFromOutputs (const Vec &input, const Vec &output, const Vec &target, Vec &costs) const
	Computes the costs from already computed output.
virtual TVec< string >	getTestCostNames () const
	Returns the names of the costs computed by computeCostsFromOutpus (and thus the test method).
virtual TVec< string >	getTrainCostNames () const
	Returns the names of the objective costs that the train method computes and for which it updates the VecStatsCollector train_stats.
Public Attributes
int	n_comp
real	sigma
Static Protected Member Functions
void	declareOptions (OptionList &ol)
	Declares this class' options.
Protected Attributes
KernelPCA	KPCA
Private Types
typedef PLearner	inherited
Private Member Functions
void	build_ ()
	This does the actual building.

Member Typedef Documentation

typedef PLearner PLearn::KPCATangentLearner::inherited [private]

Reimplemented from PLearn::PLearner.
Definition at line 58 of file KPCATangentLearner.h.

Constructor & Destructor Documentation

PLearn::KPCATangentLearner::KPCATangentLearner ( )

Default constructor.

Definition at line 54 of file KPCATangentLearner.cc.

Member Function Documentation

void PLearn::KPCATangentLearner::build ( ) [virtual]

Simply calls inherited::build() then build_().

Reimplemented from PLearn::PLearner.
Definition at line 97 of file KPCATangentLearner.cc.
References build_().

void PLearn::KPCATangentLearner::build_ ( ) [private]

This does the actual building.

Reimplemented from PLearn::PLearner.
Definition at line 85 of file KPCATangentLearner.cc.
Referenced by build().

void PLearn::KPCATangentLearner::computeCostsFromOutputs ( const Vec & input,

const Vec & output,

const Vec & target,

Vec & costs

) const [virtual]

Computes the costs from already computed output.

Implements PLearn::PLearner.
Definition at line 212 of file KPCATangentLearner.cc.

void PLearn::KPCATangentLearner::computeOutput ( const Vec & input,

Vec & output

) const [virtual]

Computes the output from the input.

Implements PLearn::PLearner.
Definition at line 151 of file KPCATangentLearner.cc.
References PLearn::KernelProjection::eigenvectors, PLearn::PLearner::inputsize(), PLearn::KernelProjection::kernel, KPCA, PLearn::VMat::length(), PLearn::Mat, n_comp, sigma, PLearn::sum(), PLearn::TMat< T >::toVec(), and PLearn::Vec.

void PLearn::KPCATangentLearner::declareOptions ( OptionList & ol ) [static, protected]

Declares this class' options.

Reimplemented from PLearn::PLearner.
Definition at line 65 of file KPCATangentLearner.cc.
References PLearn::declareOption(), and PLearn::OptionList.

void PLearn::KPCATangentLearner::forget ( ) [virtual]

(Re-)initializes the PLearner in its fresh state (that state may depend on the 'seed' option) And sets 'stage' back to 0 (this is the stage of a fresh learner!).

(Re-)initialize the PLearner in its fresh state (that state may depend on the 'seed' option) And sets 'stage' back to 0 (this is the stage of a fresh learner!)
A typical forget() method should do the following:

initialize a random number generator with the seed option
initialize the learner's parameters, using this random generator
stage = 0

Implements PLearn::PLearner.
Definition at line 126 of file KPCATangentLearner.cc.

TVec< string > PLearn::KPCATangentLearner::getTestCostNames ( ) const [virtual]

Returns the names of the costs computed by computeCostsFromOutpus (and thus the test method).

Implements PLearn::PLearner.
Definition at line 219 of file KPCATangentLearner.cc.

TVec< string > PLearn::KPCATangentLearner::getTrainCostNames ( ) const [virtual]

Returns the names of the objective costs that the train method computes and for which it updates the VecStatsCollector train_stats.

Implements PLearn::PLearner.
Definition at line 227 of file KPCATangentLearner.cc.

void PLearn::KPCATangentLearner::makeDeepCopyFromShallowCopy ( map< const void *, void * > & copies ) [virtual]

Transforms a shallow copy into a deep copy.

Definition at line 104 of file KPCATangentLearner.cc.
References PLERROR.

int PLearn::KPCATangentLearner::outputsize ( ) const [virtual]

Returns the size of this learner's output, (which typically may depend on its inputsize(), targetsize() and set options).

Implements PLearn::PLearner.
Definition at line 119 of file KPCATangentLearner.cc.
References PLearn::PLearner::inputsize(), and n_comp.