HOG2: LinearRegression Class Reference

HOG2

#include <LinearRegression.h>

Inheritance diagram for LinearRegression:

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Collaboration diagram for LinearRegression:

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Public Member Functions
	LinearRegression (int _inputs, int _outputs, double learnrate)

	LinearRegression (LinearRegression *)

	LinearRegression (char *)

	LinearRegression (FunctionApproximator *)

	~LinearRegression ()

void	setUseBinary (bool binary)

void	resizeInputs (int newSize, double newVal)

void	resizeInputs (int newSize)

void	save (const char *)

void	save (FILE *)

void	load (const char *)

void	load (FILE *)

void	load (const FunctionApproximator *fa)

void	load (const LinearRegression *)

double	train (std::vector< double > &input, std::vector< double > &output2)

double *	test (const std::vector< double > &input)

double	train (std::vector< unsigned int > &input, std::vector< double > &output2)

double *	test (const std::vector< unsigned int > &input)

void	Print ()

int	getNumInputs ()

void	setInputWeight (double value, unsigned int weightNum, unsigned int whichOutput=0)

double	getInputWeight (int inp, int outp=0)

void	getWeightUpdateVariance (std::vector< double > &var, unsigned int which=0)

double	getWeightUpdateVariance (unsigned int weightNum, unsigned int whichOutput=0)

void	getWeightUpdateAverage (std::vector< double > &var, unsigned int which=0)

double	getWeightUpdateAverage (unsigned int weightNum, unsigned int whichOutput=0)

void	getWeightUpdateSum (std::vector< double > &var, unsigned int which=0)

double	getWeightUpdateSum (unsigned int weightNum, unsigned int whichOutput=0)

void	resetWeightVariance (unsigned int weightNum, unsigned int whichOutput=0)

void	resetWeightVariance ()

int	getWeightFrequency (unsigned int weightNum, unsigned int whichOutput=0)

double	GetInput (std::vector< double > &input, const std::vector< double > &target)

Public Member Functions inherited from FunctionApproximator
	FunctionApproximator ()

virtual	~FunctionApproximator ()

virtual void	setLearnRate (double)

virtual double	getLearnRate ()

void	setOutputActivation (tActivation t)

tActivation	getOutputActivation ()

Static Public Member Functions
static bool	validSaveFile (char *fname)

Private Member Functions
void	allocateMemory ()

void	freeMemory ()

double	g (double a)

double	dg (double a)

double	outputerr (std::vector< double > &output, std::vector< double > &expected, int which)

double	error (double *output)

Private Attributes
std::vector< std::vector< double > >	weight

std::vector< std::vector< updateData > >	updates

std::vector< double >	output

int	inputs

int	outputs

bool	useBinary

Additional Inherited Members
Protected Attributes inherited from FunctionApproximator
double	rate

tActivation	outputActivation

Detailed Description

Definition at line 27 of file LinearRegression.h.

Constructor & Destructor Documentation

◆ LinearRegression() [1/4]

LinearRegression::LinearRegression	(	int	_inputs,
		int	_outputs,
		double	learnrate
	)

Definition at line 23 of file LinearRegression.cpp.

References allocateMemory(), inputs, kLinear, FunctionApproximator::outputActivation, outputs, FunctionApproximator::rate, updates, useBinary, and weight.

◆ LinearRegression() [2/4]

LinearRegression::LinearRegression ( LinearRegression * perp )

Definition at line 36 of file LinearRegression.cpp.

References load(), FunctionApproximator::outputActivation, outputs, FunctionApproximator::rate, updates, useBinary, and weight.

◆ LinearRegression() [3/4]

LinearRegression::LinearRegression ( char * f )

Definition at line 50 of file LinearRegression.cpp.

References inputs, load(), outputs, updates, useBinary, and weight.

◆ LinearRegression() [4/4]

LinearRegression::LinearRegression ( FunctionApproximator * fa )

Definition at line 60 of file LinearRegression.cpp.

References inputs, load(), FunctionApproximator::outputActivation, outputs, FunctionApproximator::rate, updates, useBinary, and weight.

◆ ~LinearRegression()

LinearRegression::~LinearRegression ( )

Definition at line 75 of file LinearRegression.cpp.

References freeMemory().

Member Function Documentation

◆ allocateMemory()

void LinearRegression::allocateMemory ( )

private

Definition at line 138 of file LinearRegression.cpp.

References inputs, output, outputs, updates, and weight.

Referenced by LinearRegression(), and load().

◆ dg()

double LinearRegression::dg ( double a )

private

◆ error()

double LinearRegression::error ( double * output )

private

◆ freeMemory()

void LinearRegression::freeMemory ( )

private

Definition at line 154 of file LinearRegression.cpp.

References updates, and weight.

Referenced by load(), and ~LinearRegression().

◆ g()

double LinearRegression::g ( double a )

private

◆ GetInput()

double LinearRegression::GetInput	(	std::vector< double > &	input,
		const std::vector< double > &	target
	)

inlinevirtual

Implements FunctionApproximator.

Definition at line 71 of file LinearRegression.h.

◆ getInputWeight()

double LinearRegression::getInputWeight	(	int	inp,
		int	outp = `0`
	)

inlinevirtual

Reimplemented from FunctionApproximator.

Definition at line 57 of file LinearRegression.h.

References weight.

◆ getNumInputs()

int LinearRegression::getNumInputs ( )

inlinevirtual

Reimplemented from FunctionApproximator.

Definition at line 55 of file LinearRegression.h.

References inputs.

◆ getWeightFrequency()

int LinearRegression::getWeightFrequency	(	unsigned int	weightNum,
		unsigned int	whichOutput = `0`
	)

Definition at line 496 of file LinearRegression.cpp.

References updates.

◆ getWeightUpdateAverage() [1/2]

void LinearRegression::getWeightUpdateAverage	(	std::vector< double > &	var,
		unsigned int	which = `0`
	)

Definition at line 437 of file LinearRegression.cpp.

References updateData::n, updateData::totErr, updates, and weight.

◆ getWeightUpdateAverage() [2/2]

double LinearRegression::getWeightUpdateAverage	(	unsigned int	weightNum,
		unsigned int	whichOutput = `0`
	)

Definition at line 451 of file LinearRegression.cpp.

References updateData::n, updateData::totErr, updates, and weight.

◆ getWeightUpdateSum() [1/2]

void LinearRegression::getWeightUpdateSum	(	std::vector< double > &	var,
		unsigned int	which = `0`
	)

Definition at line 462 of file LinearRegression.cpp.

References updates, and weight.

◆ getWeightUpdateSum() [2/2]

double LinearRegression::getWeightUpdateSum	(	unsigned int	weightNum,
		unsigned int	whichOutput = `0`
	)

Definition at line 472 of file LinearRegression.cpp.

References updates, and weight.

◆ getWeightUpdateVariance() [1/2]

void LinearRegression::getWeightUpdateVariance	(	std::vector< double > &	var,
		unsigned int	which = `0`
	)

Definition at line 412 of file LinearRegression.cpp.

References updateData::n, updateData::S, updates, and weight.

◆ getWeightUpdateVariance() [2/2]

double LinearRegression::getWeightUpdateVariance	(	unsigned int	weightNum,
		unsigned int	whichOutput = `0`
	)

Definition at line 426 of file LinearRegression.cpp.

References updateData::n, updateData::S, updates, and weight.

◆ load() [1/4]

void LinearRegression::load ( const char * fname )

virtual

Implements FunctionApproximator.

Definition at line 168 of file LinearRegression.cpp.

Referenced by LinearRegression().

◆ load() [2/4]

void LinearRegression::load ( const FunctionApproximator * fa )

inlinevirtual

Implements FunctionApproximator.

Definition at line 44 of file LinearRegression.h.

References load().

Referenced by load().

◆ load() [3/4]

void LinearRegression::load ( const LinearRegression * p )

Definition at line 241 of file LinearRegression.cpp.

References allocateMemory(), freeMemory(), inputs, FunctionApproximator::outputActivation, outputs, and weight.

◆ load() [4/4]

void LinearRegression::load ( FILE * f )

virtual

Implements FunctionApproximator.

Definition at line 188 of file LinearRegression.cpp.

References allocateMemory(), freeMemory(), inputs, little2machine(), MINVERSION, outputs, useBinary, VERSION, and weight.

◆ outputerr()

double LinearRegression::outputerr	(	std::vector< double > &	output,
		std::vector< double > &	expected,
		int	which
	)

private

Definition at line 328 of file LinearRegression.cpp.

Referenced by train().

◆ Print()

void LinearRegression::Print ( )

virtual

Implements FunctionApproximator.

Definition at line 507 of file LinearRegression.cpp.

References inputs, outputs, and weight.

◆ resetWeightVariance() [1/2]

void LinearRegression::resetWeightVariance ( )

Definition at line 485 of file LinearRegression.cpp.

References updates.

◆ resetWeightVariance() [2/2]

void LinearRegression::resetWeightVariance	(	unsigned int	weightNum,
		unsigned int	whichOutput = `0`
	)

Definition at line 480 of file LinearRegression.cpp.

References updates.

◆ resizeInputs() [1/2]

void LinearRegression::resizeInputs ( int newSize )

Definition at line 109 of file LinearRegression.cpp.

References inputs, outputs, updates, and weight.

◆ resizeInputs() [2/2]

void LinearRegression::resizeInputs	(	int	newSize,
		double	newVal
	)

Definition at line 80 of file LinearRegression.cpp.

References inputs, outputs, updates, and weight.

◆ save() [1/2]

void LinearRegression::save ( const char * fname )

virtual

Implements FunctionApproximator.

Definition at line 288 of file LinearRegression.cpp.

◆ save() [2/2]

void LinearRegression::save ( FILE * f )

virtual

Implements FunctionApproximator.

Definition at line 301 of file LinearRegression.cpp.

References inputs, little2machine(), outputs, useBinary, VERSION, and weight.

◆ setInputWeight()

void LinearRegression::setInputWeight	(	double	value,
		unsigned int	weightNum,
		unsigned int	whichOutput = `0`
	)

Definition at line 501 of file LinearRegression.cpp.

References updates, and weight.

◆ setUseBinary()

void LinearRegression::setUseBinary ( bool binary )

inline

Definition at line 35 of file LinearRegression.h.

References useBinary.

◆ test() [1/2]

double * LinearRegression::test ( const std::vector< double > & input )

virtual

Implements FunctionApproximator.

Definition at line 399 of file LinearRegression.cpp.

References inputs, output, outputs, and weight.

Referenced by train().

◆ test() [2/2]

double * LinearRegression::test ( const std::vector< unsigned int > & input )

virtual

Implements FunctionApproximator.

Definition at line 386 of file LinearRegression.cpp.

References inputs, output, outputs, and weight.

◆ train() [1/2]

double LinearRegression::train	(	std::vector< double > &	input,
		std::vector< double > &	output2
	)

virtual

Implements FunctionApproximator.

Definition at line 360 of file LinearRegression.cpp.

References inputs, updateData::mean, updateData::n, output, outputerr(), outputs, FunctionApproximator::rate, updateData::S, test(), updateData::totErr, updates, and weight.

◆ train() [2/2]

double LinearRegression::train	(	std::vector< unsigned int > &	input,
		std::vector< double > &	output2
	)

virtual

Implements FunctionApproximator.

Definition at line 335 of file LinearRegression.cpp.

References inputs, updateData::mean, updateData::n, output, outputerr(), outputs, FunctionApproximator::rate, updateData::S, test(), updateData::totErr, updates, and weight.

◆ validSaveFile()

bool LinearRegression::validSaveFile ( char * fname )

static

Definition at line 265 of file LinearRegression.cpp.

References VERSION.

Member Data Documentation

◆ inputs

int LinearRegression::inputs

private

Definition at line 89 of file LinearRegression.h.

Referenced by allocateMemory(), getNumInputs(), LinearRegression(), load(), Print(), resizeInputs(), save(), test(), and train().

◆ output

std::vector<double> LinearRegression::output

private

Definition at line 86 of file LinearRegression.h.

Referenced by allocateMemory(), test(), and train().

◆ outputs

int LinearRegression::outputs

private

Definition at line 89 of file LinearRegression.h.

Referenced by allocateMemory(), LinearRegression(), load(), Print(), resizeInputs(), save(), test(), and train().

◆ updates

std::vector<std::vector<updateData> > LinearRegression::updates

private

Definition at line 84 of file LinearRegression.h.

Referenced by allocateMemory(), freeMemory(), getWeightFrequency(), getWeightUpdateAverage(), getWeightUpdateSum(), getWeightUpdateVariance(), LinearRegression(), resetWeightVariance(), resizeInputs(), setInputWeight(), and train().

◆ useBinary

bool LinearRegression::useBinary

private

Definition at line 90 of file LinearRegression.h.

Referenced by LinearRegression(), load(), save(), and setUseBinary().

◆ weight

std::vector<std::vector<double> > LinearRegression::weight

private

Definition at line 83 of file LinearRegression.h.

Referenced by allocateMemory(), freeMemory(), getInputWeight(), getWeightUpdateAverage(), getWeightUpdateSum(), getWeightUpdateVariance(), LinearRegression(), load(), Print(), resizeInputs(), save(), setInputWeight(), test(), and train().

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

/home/sturtevant/nightly/hog2/utils/LinearRegression.h
/home/sturtevant/nightly/hog2/utils/LinearRegression.cpp