Provides some useful functions for instantiating learning algorithms from the command line. More...

#include <GLearnerLib.h>

Static Public Member Functions
static void	autoTune (GArgReader &args)

static void	autoTuneDecisionTree (GMatrix &features, GMatrix &labels)

static void	autoTuneGraphCutTransducer (GMatrix &features, GMatrix &labels)

static void	autoTuneKNN (GMatrix &features, GMatrix &labels)

static void	autoTuneNaiveBayes (GMatrix &features, GMatrix &labels)

static void	autoTuneNaiveInstance (GMatrix &features, GMatrix &labels)

static void	autoTuneNeuralNet (GMatrix &features, GMatrix &labels)

static void	CrossValidate (GArgReader &args)

static void	CrossValidateCallback (void *pSupLearner, size_t nRep, size_t nFold, double foldSSE, size_t rows)

static size_t	getAttrVal (const char *szString, size_t attrCount)

static GAgglomerativeTransducer *	InstantiateAgglomerativeTransducer (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GTransducer *	InstantiateAlgorithm (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBag *	InstantiateBag (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBaselineLearner *	InstantiateBaseline (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBayesianModelAveraging *	InstantiateBMA (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBayesianModelCombination *	InstantiateBMC (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBomb *	InstantiateBomb (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GResamplingAdaBoost *	InstantiateBoost (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBucket *	InstantiateBucket (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBucket *	InstantiateCvdt (GArgReader &args)

static GDecisionTree *	InstantiateDecisionTree (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GGaussianProcess *	InstantiateGaussianProcess (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GGraphCutTransducer *	InstantiateGraphCutTransducer (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GBayesianModelCombination *	InstantiateHodgePodge (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GKNN *	InstantiateKNN (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GLinearRegressor *	InstantiateLinearRegressor (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GMeanMarginsTree *	InstantiateMeanMarginsTree (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GNaiveBayes *	InstantiateNaiveBayes (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GNaiveInstance *	InstantiateNaiveInstance (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GNeighborTransducer *	InstantiateNeighborTransducer (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GNeuralNet *	InstantiateNeuralNet (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GRandomForest *	InstantiateRandomForest (GArgReader &args)

static GReservoirNet *	InstantiateReservoirNet (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static GWag *	InstantiateWag (GArgReader &args, GMatrix pFeatures, GMatrix pLabels)

static void	leftJustifiedString (const char pIn, char pOut, size_t outLen)

static void	loadData (GArgReader &args, Holder< GMatrix > &hFeaturesOut, Holder< GMatrix > &hLabelsOut, bool requireMetadata=false)

static std::string	machineReadableConfusionData (std::size_t variable_idx, const GRelation pRelation, GMatrix const const pMatrix)
	for variable variable_idx as printed by printMachineReadableConfusionMatrices More...

static std::string	machineReadableConfusionHeader (std::size_t variable_idx, const GRelation *pRelation)
	Returns the header for the machine readable confusion matrix for variable variable_idx as printed by printMachineReadableConfusionMatrices. More...

static void	metaData (GArgReader &args)

static void	parseAttributeList (vector< size_t > &list, GArgReader &args, size_t attrCount)

static void	PrecisionRecall (GArgReader &args)

static void	predict (GArgReader &args)

static void	predictDistribution (GArgReader &args)

static void	printConfusionMatrices (const GRelation pRelation, vector< GMatrix > &matrixArray)

static void	printMachineReadableConfusionMatrices (const GRelation pRelation, vector< GMatrix > &matrixArray)
	Prints the confusion matrices as machine-readable csv-like lines. More...

static void	regress (GArgReader &args)

static void	rightJustifiedString (const char pIn, char pOut, size_t outLen)

static void	showError (GArgReader &args, const char szAppName, const char szMessage)

static void	showInstantiateAlgorithmError (const char *szMessage, GArgReader &args)

static void	ShowUsage (const char *appName)

static void	SplitTest (GArgReader &args)

static void	sterilize (GArgReader &args)

static void	Test (GArgReader &args)

static void	Train (GArgReader &args)

static void	trainRecurrent (GArgReader &args)

static void	Transduce (GArgReader &args)

static void	TransductiveAccuracy (GArgReader &args)

static void	vette (string &s)

Detailed Description

Provides some useful functions for instantiating learning algorithms from the command line.

Member Function Documentation

static void GClasses::GLearnerLib::autoTune ( GArgReader & args )

static

static void GClasses::GLearnerLib::autoTuneDecisionTree	(	GMatrix &	features,
		GMatrix &	labels
	)

static

static void GClasses::GLearnerLib::autoTuneGraphCutTransducer	(	GMatrix &	features,
		GMatrix &	labels
	)

static

static void GClasses::GLearnerLib::autoTuneKNN	(	GMatrix &	features,
		GMatrix &	labels
	)

static

static void GClasses::GLearnerLib::autoTuneNaiveBayes	(	GMatrix &	features,
		GMatrix &	labels
	)

static

static void GClasses::GLearnerLib::autoTuneNaiveInstance	(	GMatrix &	features,
		GMatrix &	labels
	)

static

static void GClasses::GLearnerLib::autoTuneNeuralNet	(	GMatrix &	features,
		GMatrix &	labels
	)

static

static void GClasses::GLearnerLib::CrossValidate ( GArgReader & args )

static

static void GClasses::GLearnerLib::CrossValidateCallback	(	void *	pSupLearner,
		size_t	nRep,
		size_t	nFold,
		double	foldSSE,
		size_t	rows
	)

static

static size_t GClasses::GLearnerLib::getAttrVal	(	const char *	szString,
		size_t	attrCount
	)

static

static GAgglomerativeTransducer* GClasses::GLearnerLib::InstantiateAgglomerativeTransducer	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GTransducer* GClasses::GLearnerLib::InstantiateAlgorithm	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBag* GClasses::GLearnerLib::InstantiateBag	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBaselineLearner* GClasses::GLearnerLib::InstantiateBaseline	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBayesianModelAveraging* GClasses::GLearnerLib::InstantiateBMA	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBayesianModelCombination* GClasses::GLearnerLib::InstantiateBMC	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBomb* GClasses::GLearnerLib::InstantiateBomb	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GResamplingAdaBoost* GClasses::GLearnerLib::InstantiateBoost	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBucket* GClasses::GLearnerLib::InstantiateBucket	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBucket* GClasses::GLearnerLib::InstantiateCvdt ( GArgReader & args )

static

static GDecisionTree* GClasses::GLearnerLib::InstantiateDecisionTree	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GGaussianProcess* GClasses::GLearnerLib::InstantiateGaussianProcess	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GGraphCutTransducer* GClasses::GLearnerLib::InstantiateGraphCutTransducer	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GBayesianModelCombination* GClasses::GLearnerLib::InstantiateHodgePodge	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GKNN* GClasses::GLearnerLib::InstantiateKNN	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GLinearRegressor* GClasses::GLearnerLib::InstantiateLinearRegressor	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GMeanMarginsTree* GClasses::GLearnerLib::InstantiateMeanMarginsTree	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GNaiveBayes* GClasses::GLearnerLib::InstantiateNaiveBayes	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GNaiveInstance* GClasses::GLearnerLib::InstantiateNaiveInstance	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GNeighborTransducer* GClasses::GLearnerLib::InstantiateNeighborTransducer	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GNeuralNet* GClasses::GLearnerLib::InstantiateNeuralNet	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GRandomForest* GClasses::GLearnerLib::InstantiateRandomForest ( GArgReader & args )

static

static GReservoirNet* GClasses::GLearnerLib::InstantiateReservoirNet	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static GWag* GClasses::GLearnerLib::InstantiateWag	(	GArgReader &	args,
		GMatrix *	pFeatures,
		GMatrix *	pLabels
	)

static

static void GClasses::GLearnerLib::leftJustifiedString	(	const char *	pIn,
		char *	pOut,
		size_t	outLen
	)

static

static void GClasses::GLearnerLib::loadData	(	GArgReader &	args,
		Holder< GMatrix > &	hFeaturesOut,
		Holder< GMatrix > &	hLabelsOut,
		bool	requireMetadata = `false`
	)

static

static std::string GClasses::GLearnerLib::machineReadableConfusionData	(	std::size_t	variable_idx,
		const GRelation *	pRelation,
		GMatrix const *const	pMatrix
	)

static

for variable variable_idx as printed by printMachineReadableConfusionMatrices

The first entry is the name of the variable. The second entry is the value of variable_idx, The entry (r*numCols+c)+2 where r and c are both in 0..nv-1, nv being the number of values that the variable takes on, is the entry at row r and column c of *pMatrix

Parameters

variable_idx	the index of the variable in the relation
pRelation	a pointer to the relation from which the variable_idx-'th variable is taken. Cannot be NULL.
pMatrix	a pointer to the confusion matrix. (*pMatrix)[r][c] is the number of times that r was expected and c was received. Cannot be NULL.

static std::string GClasses::GLearnerLib::machineReadableConfusionHeader	(	std::size_t	variable_idx,
		const GRelation *	pRelation
	)

static

Returns the header for the machine readable confusion matrix for variable variable_idx as printed by printMachineReadableConfusionMatrices.

The header is comma-separated values. The first two entries in the header are "Variable Name","Variable Index". The rest of the entries fit the format "Expected:xxx/Got:yyy" where xxx and yyy are two values that the variable can take on.

Parameters

variable_idx	the index of the variable in the relation
pRelation	a pointer to the relation from which the variable_idx-'th variable is taken. Cannot be null

static void GClasses::GLearnerLib::metaData ( GArgReader & args )

static

static void GClasses::GLearnerLib::parseAttributeList	(	vector< size_t > &	list,
		GArgReader &	args,
		size_t	attrCount
	)

static

static void GClasses::GLearnerLib::PrecisionRecall ( GArgReader & args )

static

static void GClasses::GLearnerLib::predict ( GArgReader & args )

static

static void GClasses::GLearnerLib::predictDistribution ( GArgReader & args )

static

static void GClasses::GLearnerLib::printConfusionMatrices	(	const GRelation *	pRelation,
		vector< GMatrix * > &	matrixArray
	)

static

static void GClasses::GLearnerLib::printMachineReadableConfusionMatrices	(	const GRelation *	pRelation,
		vector< GMatrix * > &	matrixArray
	)

static

Prints the confusion matrices as machine-readable csv-like lines.

The first line is a header giving the names of the columns for the next line. The first column is the name of the label variable for which the matrix is being printed. The rest of the columns are the names of the expected/got values (row/column in the input matrices)

Parameters

pRelation	the relation for which the confusion matrices are given. Cannot be NULL.
matrixArray	matrixArray[i] is null if there is no matrix to be printed. Otherwise matrixArray[i] is the confusion matrix for the i'th attribute of pRelation. Row r, column c of matrixArray[i] is the number of times the value r of the attribute was expected and c was encountered.

static void GClasses::GLearnerLib::regress ( GArgReader & args )

static

static void GClasses::GLearnerLib::rightJustifiedString	(	const char *	pIn,
		char *	pOut,
		size_t	outLen
	)

static

static void GClasses::GLearnerLib::showError	(	GArgReader &	args,
		const char *	szAppName,
		const char *	szMessage
	)

static

static void GClasses::GLearnerLib::showInstantiateAlgorithmError	(	const char *	szMessage,
		GArgReader &	args
	)

static

static void GClasses::GLearnerLib::ShowUsage ( const char * appName )

static

static void GClasses::GLearnerLib::SplitTest ( GArgReader & args )

static

static void GClasses::GLearnerLib::sterilize ( GArgReader & args )

static

static void GClasses::GLearnerLib::Test ( GArgReader & args )

static

static void GClasses::GLearnerLib::Train ( GArgReader & args )

static

static void GClasses::GLearnerLib::trainRecurrent ( GArgReader & args )

static

static void GClasses::GLearnerLib::Transduce ( GArgReader & args )

static

static void GClasses::GLearnerLib::TransductiveAccuracy ( GArgReader & args )

static

static void GClasses::GLearnerLib::vette ( string & s )

static

Static Public Member Functions

Detailed Description

Member Function Documentation