GClasses
GClasses::GLearnerLib Class Reference

Detailed Description

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

#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 GAgglomerativeTransducerInstantiateAgglomerativeTransducer (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GTransducerInstantiateAlgorithm (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBagInstantiateBag (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBaselineLearnerInstantiateBaseline (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBlockinstantiateBlock (GArgReader &args)
 
static GBayesianModelAveragingInstantiateBMA (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBayesianModelCombinationInstantiateBMC (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBombInstantiateBomb (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GResamplingAdaBoostInstantiateBoost (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBucketInstantiateBucket (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBucketInstantiateCvdt (GArgReader &args)
 
static GDecisionTreeInstantiateDecisionTree (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GGaussianProcessInstantiateGaussianProcess (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GGraphCutTransducerInstantiateGraphCutTransducer (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GBayesianModelCombinationInstantiateHodgePodge (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GKNNInstantiateKNN (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GLinearRegressorInstantiateLinearRegressor (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GMeanMarginsTreeInstantiateMeanMarginsTree (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GNaiveBayesInstantiateNaiveBayes (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GNaiveInstanceInstantiateNaiveInstance (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GNeighborTransducerInstantiateNeighborTransducer (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GNeuralNetLearnerInstantiateNeuralNet (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GRandomForestInstantiateRandomForest (GArgReader &args)
 
static GReservoirNetInstantiateReservoirNet (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static GWagInstantiateWag (GArgReader &args, GMatrix *pFeatures, GMatrix *pLabels)
 
static void leftJustifiedString (const char *pIn, char *pOut, size_t outLen)
 
static void loadData (GArgReader &args, std::unique_ptr< GMatrix > &hFeaturesOut, std::unique_ptr< 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 Transduce (GArgReader &args)
 
static void TransductiveAccuracy (GArgReader &args)
 
static void vette (string &s)
 

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 GBlock* GClasses::GLearnerLib::instantiateBlock ( GArgReader args)
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 GNeuralNetLearner* 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,
std::unique_ptr< GMatrix > &  hFeaturesOut,
std::unique_ptr< 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_idxthe index of the variable in the relation
pRelationa pointer to the relation from which the variable_idx-'th variable is taken. Cannot be NULL.
pMatrixa 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_idxthe index of the variable in the relation
pRelationa 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
pRelationthe relation for which the confusion matrices are given. Cannot be NULL.
matrixArraymatrixArray[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::Transduce ( GArgReader args)
static
static void GClasses::GLearnerLib::TransductiveAccuracy ( GArgReader args)
static
static void GClasses::GLearnerLib::vette ( string &  s)
static