PLearn::ClassifierFromDensity Class Reference

#include <ClassifierFromDensity.h>

Inheritance diagram for PLearn::ClassifierFromDensity:

[legend]Collaboration diagram for PLearn::ClassifierFromDensity:

[legend]List of all members.


Public Types
typedef PLearner	inherited
Public Member Functions
	ClassifierFromDensity ()
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 (ClassifierFromDensity)
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	nclasses
TVec< PP< PLearner > >	estimators
Vec	log_priors
bool	output_log_probabilities
bool	normalize_probabilities
Static Protected Member Functions
void	declareOptions (OptionList &ol)
	Declares this class' options.
Private Member Functions
void	build_ ()
	This does the actual building.

Member Typedef Documentation

typedef PLearner PLearn::ClassifierFromDensity::inherited

Reimplemented from PLearn::PLearner.
Definition at line 53 of file ClassifierFromDensity.h.

Constructor & Destructor Documentation

PLearn::ClassifierFromDensity::ClassifierFromDensity ( )

Definition at line 51 of file ClassifierFromDensity.cc.

Member Function Documentation

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

simply calls inherited::build() then build_()

Reimplemented from PLearn::PLearner.
Definition at line 93 of file ClassifierFromDensity.cc.
References build_().

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

This does the actual building.

Reimplemented from PLearn::PLearner.
Definition at line 80 of file ClassifierFromDensity.cc.
References PLearn::deepCopy(), estimators, nclasses, PLERROR, PLearn::TVec< PP< PLearner > >::resize(), and PLearn::TVec< PP< PLearner > >::size().
Referenced by build().

void PLearn::ClassifierFromDensity::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 210 of file ClassifierFromDensity.cc.
References PLearn::class_error(), PLearn::condprob_cost(), PLearn::CostFunc, and PLearn::TVec< T >::resize().

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

Vec & output

) const [virtual]

Computes the output from the input.

Implements PLearn::PLearner.
Definition at line 172 of file ClassifierFromDensity.cc.
References estimators, PLearn::exp(), log_priors, PLearn::logadd(), nclasses, normalize_probabilities, output_log_probabilities, and PLearn::TVec< T >::resize().

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

Declares this class' options.

Reimplemented from PLearn::PLearner.
Definition at line 62 of file ClassifierFromDensity.cc.
References PLearn::declareOption(), and PLearn::OptionList.

void PLearn::ClassifierFromDensity::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.
Definition at line 113 of file ClassifierFromDensity.cc.
References estimators, and PLearn::TVec< PP< PLearner > >::length().
Referenced by train().

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

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

Implements PLearn::PLearner.
Definition at line 225 of file ClassifierFromDensity.cc.

TVec< string > PLearn::ClassifierFromDensity::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 233 of file ClassifierFromDensity.cc.

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

Transforms a shallow copy into a deep copy.

Definition at line 100 of file ClassifierFromDensity.cc.
References PLearn::deepCopyField(), estimators, and log_priors.

int PLearn::ClassifierFromDensity::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 108 of file ClassifierFromDensity.cc.
References nclasses.