PLearn::KernelProjection Class Reference

#include <KernelProjection.h>

Inheritance diagram for PLearn::KernelProjection:

[legend]Collaboration diagram for PLearn::KernelProjection:

[legend]List of all members.


Public Member Functions
	KernelProjection ()
	Default constructor.
virtual Vec	getEigenvalues ()
	Return the eigenvalues of this learner.
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 (KernelProjection)
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.
virtual void	setTrainingSet (VMat training_set, bool call_forget=true)
	Overridden to forward to the kernel.
Public Attributes
bool	compute_costs
bool	free_extra_components
int	ignore_n_first
Ker	kernel
real	min_eigenvalue
int	n_comp
int	n_comp_for_cost
int	normalize
Vec	eigenvalues
Mat	eigenvectors
Static Protected Member Functions
void	declareOptions (OptionList &ol)
	Declares this class' options.
Protected Attributes
int	n_comp_kept
int	n_examples
bool	first_output
	A boolean indicating we haven't performed any output yet.
Vec	last_input
	The last input given when computing costs.
Vec	last_output
	The last output computed when computing costs.
Private Types
typedef PLearner	inherited
Private Member Functions
void	build_ ()
	This does the actual building.
Private Attributes
Vec	k_x_xi
	Global storage to save memory allocations.
Mat	result
Mat	used_eigenvectors

Member Typedef Documentation

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

Reimplemented from PLearn::PLearner.
Reimplemented in PLearn::Isomap, PLearn::KernelPCA, PLearn::LLE, and PLearn::SpectralClustering.
Definition at line 58 of file KernelProjection.h.

Constructor & Destructor Documentation

PLearn::KernelProjection::KernelProjection ( )

Default constructor.

Definition at line 53 of file KernelProjection.cc.
References PLearn::normalize(), and REAL_MAX.

Member Function Documentation

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

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

Reimplemented from PLearn::PLearner.
Reimplemented in PLearn::Isomap, PLearn::KernelPCA, PLearn::LLE, and PLearn::SpectralClustering.
Definition at line 129 of file KernelProjection.cc.
References build_().

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

This does the actual building.

Reimplemented from PLearn::PLearner.
Reimplemented in PLearn::Isomap, PLearn::KernelPCA, PLearn::LLE, and PLearn::SpectralClustering.
Definition at line 138 of file KernelProjection.cc.
References first_output, last_input, n_comp, n_comp_kept, normalize, PLERROR, and PLearn::TVec< T >::resize().
Referenced by build().

void PLearn::KernelProjection::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 157 of file KernelProjection.cc.
References PLearn::abs(), compute_costs, PLearn::dot(), PLearn::endl(), kernel, last_input, last_output, PLearn::TVec< T >::length(), MISSING_VALUE, n_comp_for_cost, PLearn::pownorm(), PLearn::TVec< T >::resize(), and PLearn::TVec< T >::subVec().

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

Vec & output

) const [virtual]

Computes the output from the input.

Implements PLearn::PLearner.
Definition at line 201 of file KernelProjection.cc.
References eigenvalues, eigenvectors, first_output, k_x_xi, kernel, n_comp_kept, n_examples, normalize, PLERROR, PLearn::TMat< T >::resize(), PLearn::TVec< T >::resize(), result, PLearn::rowSum(), PLearn::sqrt(), PLearn::TMat< T >::subMatRows(), and used_eigenvectors.

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

Declares this class' options.

Reimplemented from PLearn::PLearner.
Reimplemented in PLearn::Isomap, PLearn::KernelPCA, PLearn::LLE, and PLearn::SpectralClustering.
Definition at line 75 of file KernelProjection.cc.
References PLearn::declareOption(), and PLearn::OptionList.

void PLearn::KernelProjection::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!).

Implements PLearn::PLearner.
Reimplemented in PLearn::Isomap, PLearn::KernelPCA, PLearn::LLE, and PLearn::SpectralClustering.
Definition at line 237 of file KernelProjection.cc.
References eigenvalues, eigenvectors, first_output, last_input, PLearn::Mat, n_comp, n_comp_kept, n_examples, PLearn::TVec< T >::resize(), and PLearn::Vec.

virtual Vec PLearn::KernelProjection::getEigenvalues ( ) [inline, virtual]

Return the eigenvalues of this learner.

Definition at line 128 of file KernelProjection.h.
References eigenvalues.

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

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

Implements PLearn::PLearner.
Definition at line 252 of file KernelProjection.cc.
References PLearn::TVec< T >::append(), and compute_costs.
Referenced by getTrainCostNames().

TVec< string > PLearn::KernelProjection::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 269 of file KernelProjection.cc.
References getTestCostNames().

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

Transforms a shallow copy into a deep copy.

Reimplemented in PLearn::Isomap, PLearn::KernelPCA, PLearn::LLE, and PLearn::SpectralClustering.
Definition at line 277 of file KernelProjection.cc.
References PLERROR.

int PLearn::KernelProjection::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 295 of file KernelProjection.cc.
References n_comp_kept.

PLearn::KernelProjection::PLEARN_DECLARE_OBJECT ( KernelProjection )

void PLearn::KernelProjection::setTrainingSet ( VMat training_set,

bool call_forget = true

) [virtual]

Overridden to forward to the kernel.

Reimplemented from PLearn::PLearner.
Definition at line 303 of file KernelProjection.cc.
References kernel, PLearn::VMat::length(), n_examples, and PLERROR.
Referenced by PLearn::IsomapTangentLearner::build_(), and PLearn::KPCATangentLearner::train().

void PLearn::KernelProjection::train ( ) [virtual]

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.

Implements PLearn::PLearner.
Definition at line 320 of file KernelProjection.cc.
References eigenvalues, PLearn::eigenVecOfSymmMat(), eigenvectors, PLearn::endl(), first_output, PLearn::flush(), free_extra_components, ignore_n_first, kernel, PLearn::TMat< T >::length(), PLearn::TVec< T >::length(), min_eigenvalue, n_comp, n_comp_kept, n_examples, PLWARNING, PLearn::TMat< T >::resize(), PLearn::TVec< T >::resize(), PLearn::TMat< T >::subMatRows(), PLearn::TVec< T >::subVec(), and PLearn::TMat< T >::width().
Referenced by PLearn::KPCATangentLearner::train(), and PLearn::IsomapTangentLearner::train().

Member Data Documentation

bool PLearn::KernelProjection::compute_costs

Definition at line 88 of file KernelProjection.h.
Referenced by computeCostsFromOutputs(), and getTestCostNames().

Vec PLearn::KernelProjection::eigenvalues

Definition at line 101 of file KernelProjection.h.
Referenced by computeOutput(), forget(), getEigenvalues(), and train().

Mat PLearn::KernelProjection::eigenvectors

Definition at line 102 of file KernelProjection.h.
Referenced by PLearn::KPCATangentLearner::computeOutput(), computeOutput(), PLearn::IsomapTangentLearner::computeOutput(), forget(), and train().

bool PLearn::KernelProjection::first_output [mutable, protected]

A boolean indicating we haven't performed any output yet.

Definition at line 77 of file KernelProjection.h.
Referenced by build_(), computeOutput(), forget(), and train().

bool PLearn::KernelProjection::free_extra_components

Definition at line 89 of file KernelProjection.h.
Referenced by train().

int PLearn::KernelProjection::ignore_n_first

Definition at line 90 of file KernelProjection.h.
Referenced by train().

Vec PLearn::KernelProjection::k_x_xi [mutable, private]

Global storage to save memory allocations.

Definition at line 61 of file KernelProjection.h.
Referenced by computeOutput().

Ker PLearn::KernelProjection::kernel

Definition at line 91 of file KernelProjection.h.
Referenced by computeCostsFromOutputs(), PLearn::KPCATangentLearner::computeOutput(), computeOutput(), PLearn::IsomapTangentLearner::computeOutput(), setTrainingSet(), and train().

Vec PLearn::KernelProjection::last_input [mutable, protected]

The last input given when computing costs.

Definition at line 79 of file KernelProjection.h.
Referenced by build_(), computeCostsFromOutputs(), and forget().

Vec PLearn::KernelProjection::last_output [mutable, protected]

The last output computed when computing costs.

Definition at line 80 of file KernelProjection.h.
Referenced by computeCostsFromOutputs().

real PLearn::KernelProjection::min_eigenvalue

Definition at line 92 of file KernelProjection.h.
Referenced by train().

int PLearn::KernelProjection::n_comp

Definition at line 93 of file KernelProjection.h.
Referenced by build_(), PLearn::IsomapTangentLearner::build_(), forget(), PLearn::KPCATangentLearner::train(), and train().

int PLearn::KernelProjection::n_comp_for_cost

Definition at line 94 of file KernelProjection.h.
Referenced by computeCostsFromOutputs().

int PLearn::KernelProjection::n_comp_kept [protected]

Definition at line 71 of file KernelProjection.h.
Referenced by build_(), computeOutput(), forget(), outputsize(), and train().

int PLearn::KernelProjection::n_examples [protected]

Reimplemented from PLearn::PLearner.
Definition at line 72 of file KernelProjection.h.
Referenced by computeOutput(), forget(), setTrainingSet(), and train().

int PLearn::KernelProjection::normalize

Definition at line 95 of file KernelProjection.h.
Referenced by build_(), and computeOutput().

Mat PLearn::KernelProjection::result [mutable, private]

Definition at line 62 of file KernelProjection.h.
Referenced by computeOutput().

Mat PLearn::KernelProjection::used_eigenvectors [mutable, private]

Definition at line 63 of file KernelProjection.h.
Referenced by computeOutput().

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

Generated on Tue Aug 17 16:27:57 2004 for PLearn by

1.3.7

PLearn::KernelProjection Class Reference

Public Member Functions

Public Attributes

Static Protected Member Functions

Protected Attributes

Private Types

Private Member Functions

Private Attributes

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation