PLearn::ConstantRegressor Class Reference

#include <ConstantRegressor.h>

Inheritance diagram for PLearn::ConstantRegressor:

[legend]Collaboration diagram for PLearn::ConstantRegressor:

[legend]List of all members.

Public Member Functions
	ConstantRegressor ()
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 (ConstantRegressor)
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
real	weight_decay
	Weight decay; not usually useful but...
Static Protected Member Functions
void	declareOptions (OptionList &ol)
	Declares this class' options.
Protected Attributes
Vec	constant_output
Private Types
typedef PLearner	inherited
Private Member Functions
void	build_ ()
	This does the actual building.

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Member Typedef Documentation

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

Reimplemented from PLearn::PLearner. Definition at line 52 of file ConstantRegressor.h.

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Constructor & Destructor Documentation

PLearn::ConstantRegressor::ConstantRegressor (   )

Definition at line 46 of file ConstantRegressor.cc.

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Member Function Documentation

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

simply calls inherited::build() then build_() Reimplemented from PLearn::PLearner. Definition at line 93 of file ConstantRegressor.cc. References build_().

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

This does the actual building. Reimplemented from PLearn::PLearner. Definition at line 88 of file ConstantRegressor.cc. Referenced by build().

void PLearn::ConstantRegressor::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 160 of file ConstantRegressor.cc. References PLearn::powdistance().

void PLearn::ConstantRegressor::computeOutput (  const Vec &  input, Vec &  output )  const [virtual]

Computes the output from the input. Implements PLearn::PLearner. Definition at line 153 of file ConstantRegressor.cc. References constant_output, outputsize(), and PLearn::TVec< T >::resize().

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

Declares this class' options. Reimplemented from PLearn::PLearner. Definition at line 65 of file ConstantRegressor.cc. References PLearn::declareOption(), and PLearn::OptionList.

void PLearn::ConstantRegressor::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 111 of file ConstantRegressor.cc.

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

Returns the names of the costs computed by computeCostsFromOutpus (and thus the test method). Implements PLearn::PLearner. Definition at line 167 of file ConstantRegressor.cc. References getTrainCostNames().

TVec< string > PLearn::ConstantRegressor::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 173 of file ConstantRegressor.cc. Referenced by getTestCostNames().

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

Transforms a shallow copy into a deep copy. Definition at line 100 of file ConstantRegressor.cc.

int PLearn::ConstantRegressor::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 106 of file ConstantRegressor.cc. References PLearn::PLearner::targetsize(). Referenced by computeOutput().

PLearn::ConstantRegressor::PLEARN_DECLARE_OBJECT (  ConstantRegressor   )

void PLearn::ConstantRegressor::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 116 of file ConstantRegressor.cc. References PLearn::TVec< T >::clear(), constant_output, PLearn::VMat::getExample(), PLearn::PLearner::inputsize(), PLearn::VMat::length(), PLearn::multiply(), PLearn::multiplyAdd(), PLearn::powdistance(), PLearn::TVec< T >::resize(), PLearn::PLearner::targetsize(), and PLearn::Vec.

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Member Data Documentation

Vec PLearn::ConstantRegressor::constant_output [protected]

Definition at line 60 of file ConstantRegressor.h. Referenced by computeOutput(), and train().

real PLearn::ConstantRegressor::weight_decay

Weight decay; not usually useful but... Definition at line 65 of file ConstantRegressor.h.

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

• ConstantRegressor.h
• ConstantRegressor.cc

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