, including all inherited members.
accuracy(GMatrix &features, GMatrix &labels, double *pOutResults, std::vector< GMatrix * > *pNominalLabelStats=NULL) | GClasses::GSupervisedLearner | |
baseDomNode(GDom *pDoc, const char *szClassName) | GClasses::GSupervisedLearner | [protected] |
basicTest(double minAccuracy1, double minAccuracy2, double deviation=1e-6, bool printAccuracy=false) | GClasses::GSupervisedLearner | |
beginIncrementalLearning(sp_relation &pFeatureRel, sp_relation &pLabelRel) | GClasses::GIncrementalLearner | |
beginIncrementalLearningInner(sp_relation &pFeatureRel, sp_relation &pLabelRel)=0 | GClasses::GIncrementalLearner | [protected, pure virtual] |
calibrate(GMatrix &features, GMatrix &labels) | GClasses::GSupervisedLearner | |
canGeneralize() | GClasses::GSupervisedLearner | [inline, virtual] |
canImplicitlyHandleContinuousFeatures() | GClasses::GTransducer | [inline, protected, virtual] |
canImplicitlyHandleContinuousLabels() | GClasses::GTransducer | [inline, protected, virtual] |
canImplicitlyHandleMissingFeatures() | GClasses::GTransducer | [inline, protected, virtual] |
canImplicitlyHandleNominalFeatures() | GClasses::GTransducer | [inline, protected, virtual] |
canImplicitlyHandleNominalLabels() | GClasses::GTransducer | [inline, protected, virtual] |
canTrainIncrementally() | GClasses::GIncrementalLearner | [inline, virtual] |
clear()=0 | GClasses::GSupervisedLearner | [pure virtual] |
crossValidate(GMatrix &features, GMatrix &labels, size_t nFolds, RepValidateCallback pCB=NULL, size_t nRep=0, void *pThis=NULL) | GClasses::GTransducer | |
featureDims() | GClasses::GSupervisedLearner | [inline] |
featureFilter() | GClasses::GSupervisedLearner | [inline] |
GIncrementalLearner(GRand &rand) | GClasses::GIncrementalLearner | [inline] |
GIncrementalLearner(GDomNode *pNode, GLearnerLoader &ll) | GClasses::GIncrementalLearner | [inline] |
GSupervisedLearner(GRand &rand) | GClasses::GSupervisedLearner | |
GSupervisedLearner(GDomNode *pNode, GLearnerLoader &ll) | GClasses::GSupervisedLearner | |
GTransducer(GRand &rand) | GClasses::GTransducer | |
heuristicValidate(GMatrix &features, GMatrix &labels) | GClasses::GTransducer | |
isFilter() | GClasses::GIncrementalLearner | [inline, virtual] |
labelDims() | GClasses::GSupervisedLearner | [inline] |
labelFilter() | GClasses::GSupervisedLearner | [inline] |
m_autoFilter | GClasses::GSupervisedLearner | [protected] |
m_featureDims | GClasses::GSupervisedLearner | [protected] |
m_labelDims | GClasses::GSupervisedLearner | [protected] |
m_pCalibrations | GClasses::GSupervisedLearner | [protected] |
m_pFeatureFilter | GClasses::GSupervisedLearner | [protected] |
m_pLabelFilter | GClasses::GSupervisedLearner | [protected] |
m_rand | GClasses::GTransducer | [protected] |
precisionRecall(double *pOutPrecision, size_t nPrecisionSize, GMatrix &features, GMatrix &labels, size_t label, size_t nReps) | GClasses::GSupervisedLearner | |
precisionRecallContinuous(GPrediction *pOutput, double *pFunc, GMatrix &trainFeatures, GMatrix &trainLabels, GMatrix &testFeatures, GMatrix &testLabels, size_t label) | GClasses::GSupervisedLearner | [protected] |
precisionRecallNominal(GPrediction *pOutput, double *pFunc, GMatrix &trainFeatures, GMatrix &trainLabels, GMatrix &testFeatures, GMatrix &testLabels, size_t label, int value) | GClasses::GSupervisedLearner | [protected] |
predict(const double *pIn, double *pOut) | GClasses::GSupervisedLearner | |
predictDistribution(const double *pIn, GPrediction *pOut) | GClasses::GSupervisedLearner | |
predictDistributionInner(const double *pIn, GPrediction *pOut)=0 | GClasses::GSupervisedLearner | [protected, pure virtual] |
predictInner(const double *pIn, double *pOut)=0 | GClasses::GSupervisedLearner | [protected, pure virtual] |
rand() | GClasses::GTransducer | [inline] |
repValidate(GMatrix &features, GMatrix &labels, size_t reps, size_t nFolds, RepValidateCallback pCB=NULL, void *pThis=NULL) | GClasses::GTransducer | |
serialize(GDom *pDoc)=0 | GClasses::GSupervisedLearner | [pure virtual] |
setAutoFilter(bool b) | GClasses::GSupervisedLearner | [inline] |
setFeatureFilter(GTwoWayIncrementalTransform *pFilter) | GClasses::GSupervisedLearner | |
setLabelFilter(GTwoWayIncrementalTransform *pFilter) | GClasses::GSupervisedLearner | |
setupFilters(GMatrix &features, GMatrix &labels) | GClasses::GSupervisedLearner | [protected] |
supportedFeatureRange(double *pOutMin, double *pOutMax) | GClasses::GTransducer | [inline, protected, virtual] |
supportedLabelRange(double *pOutMin, double *pOutMax) | GClasses::GTransducer | [inline, protected, virtual] |
test() | GClasses::GSupervisedLearner | [static] |
train(GMatrix &features, GMatrix &labels) | GClasses::GSupervisedLearner | |
trainAndTest(GMatrix &trainFeatures, GMatrix &trainLabels, GMatrix &testFeatures, GMatrix &testLabels, double *pOutResults, std::vector< GMatrix * > *pNominalLabelStats=NULL) | GClasses::GSupervisedLearner | [virtual] |
trainIncremental(const double *pIn, const double *pOut) | GClasses::GIncrementalLearner | |
trainIncrementalInner(const double *pIn, const double *pOut)=0 | GClasses::GIncrementalLearner | [protected, pure virtual] |
trainInner(GMatrix &features, GMatrix &labels)=0 | GClasses::GSupervisedLearner | [protected, pure virtual] |
trainSparse(GSparseMatrix &features, GMatrix &labels)=0 | GClasses::GIncrementalLearner | [pure virtual] |
transduce(GMatrix &features1, GMatrix &labels1, GMatrix &features2) | GClasses::GTransducer | |
transduceInner(GMatrix &features1, GMatrix &labels1, GMatrix &features2) | GClasses::GSupervisedLearner | [protected, virtual] |
~GIncrementalLearner() | GClasses::GIncrementalLearner | [inline, virtual] |
~GSupervisedLearner() | GClasses::GSupervisedLearner | [virtual] |
~GTransducer() | GClasses::GTransducer | [virtual] |