GClasses

GClasses::GNeuralNet Member List

This is the complete list of members for GClasses::GNeuralNet, including all inherited members.
accuracy(GMatrix &features, GMatrix &labels, double *pOutResults, std::vector< GMatrix * > *pNominalLabelStats=NULL)GClasses::GSupervisedLearner
addLayer(size_t nNodes)GClasses::GNeuralNet
addNode(size_t layer)GClasses::GNeuralNet
align(GNeuralNet &that)GClasses::GNeuralNet
autoTune(GMatrix &features, GMatrix &labels)GClasses::GNeuralNet
backProp()GClasses::GNeuralNet [inline]
backPropTargetFunction()GClasses::GNeuralNet [inline]
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)GClasses::GNeuralNet [protected, 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::GNeuralNet [inline, protected, virtual]
canImplicitlyHandleNominalFeatures()GClasses::GNeuralNet [inline, protected, virtual]
canImplicitlyHandleNominalLabels()GClasses::GNeuralNet [inline, protected, virtual]
canTrainIncrementally()GClasses::GIncrementalLearner [inline, virtual]
clear()GClasses::GNeuralNet [inline, virtual]
clipWeights(double max)GClasses::GNeuralNet
copyPrediction(double *pOut)GClasses::GNeuralNet
copyStructure(GNeuralNet *pOther)GClasses::GNeuralNet
copyWeights(GNeuralNet *pOther)GClasses::GNeuralNet
countWeights()GClasses::GNeuralNet
cross_entropy enum valueGClasses::GNeuralNet
crossValidate(GMatrix &features, GMatrix &labels, size_t nFolds, RepValidateCallback pCB=NULL, size_t nRep=0, void *pThis=NULL)GClasses::GTransducer
decayWeights(double lambda, double gamma=1.0)GClasses::GNeuralNet
decayWeightsSingleOutput(size_t output, double lambda)GClasses::GNeuralNet
dropNode(size_t layer, size_t node)GClasses::GNeuralNet
featureDims()GClasses::GSupervisedLearner [inline]
featureFilter()GClasses::GSupervisedLearner [inline]
forwardProp(const double *pInputs)GClasses::GNeuralNet
forwardPropSingleOutput(const double *pInputs, size_t output)GClasses::GNeuralNet
GBackProp classGClasses::GNeuralNet [friend]
GIncrementalLearner(GRand &rand)GClasses::GIncrementalLearner [inline]
GIncrementalLearner(GDomNode *pNode, GLearnerLoader &ll)GClasses::GIncrementalLearner [inline]
GNeuralNet(GRand &rand)GClasses::GNeuralNet
GNeuralNet(GDomNode *pNode, GLearnerLoader &ll)GClasses::GNeuralNet
GSupervisedLearner(GRand &rand)GClasses::GSupervisedLearner
GSupervisedLearner(GDomNode *pNode, GLearnerLoader &ll)GClasses::GSupervisedLearner
GTransducer(GRand &rand)GClasses::GTransducer
hasTrainingBegun()GClasses::GNeuralNet [inline]
heuristicValidate(GMatrix &features, GMatrix &labels)GClasses::GTransducer
improvementThresh()GClasses::GNeuralNet [inline]
internalTraininGMatrix()GClasses::GNeuralNet
internalValidationData()GClasses::GNeuralNet
isFilter()GClasses::GIncrementalLearner [inline, virtual]
labelDims()GClasses::GSupervisedLearner [inline]
labelFilter()GClasses::GSupervisedLearner [inline]
layer(size_t n)GClasses::GNeuralNet [inline]
layerCount()GClasses::GNeuralNet [inline]
learningRate()GClasses::GNeuralNet [inline]
m_activationFunctionsGClasses::GNeuralNet [protected]
m_autoFilterGClasses::GSupervisedLearner [protected]
m_backPropTargetFunctionGClasses::GNeuralNet [protected]
m_epochsPerValidationCheckGClasses::GNeuralNet [protected]
m_featureDimsGClasses::GSupervisedLearner [protected]
m_internalFeatureDimsGClasses::GNeuralNet [protected]
m_internalLabelDimsGClasses::GNeuralNet [protected]
m_labelDimsGClasses::GSupervisedLearner [protected]
m_layersGClasses::GNeuralNet [protected]
m_learningRateGClasses::GNeuralNet [protected]
m_minImprovementGClasses::GNeuralNet [protected]
m_momentumGClasses::GNeuralNet [protected]
m_pActivationFunctionGClasses::GNeuralNet [protected]
m_pBackPropGClasses::GNeuralNet [protected]
m_pCalibrationsGClasses::GSupervisedLearner [protected]
m_pFeatureFilterGClasses::GSupervisedLearner [protected]
m_pLabelFilterGClasses::GSupervisedLearner [protected]
m_randGClasses::GTransducer [protected]
m_useInputBiasGClasses::GNeuralNet [protected]
m_validationPortionGClasses::GNeuralNet [protected]
momentum()GClasses::GNeuralNet [inline]
perturbAllWeights(double deviation)GClasses::GNeuralNet
physical enum valueGClasses::GNeuralNet
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)GClasses::GNeuralNet [protected, virtual]
predictInner(const double *pIn, double *pOut)GClasses::GNeuralNet [protected, virtual]
rand()GClasses::GTransducer [inline]
releaseTrainingJunk()GClasses::GNeuralNet
repValidate(GMatrix &features, GMatrix &labels, size_t reps, size_t nFolds, RepValidateCallback pCB=NULL, void *pThis=NULL)GClasses::GTransducer
serialize(GDom *pDoc)GClasses::GNeuralNet [virtual]
setActivationFunction(GActivationFunction *pSF, bool hold)GClasses::GNeuralNet
setAutoFilter(bool b)GClasses::GSupervisedLearner [inline]
setBackPropTargetFunction(TargetFunction eTF)GClasses::GNeuralNet [inline]
setErrorOnOutputLayer(const double *pTarget, TargetFunction eTargetFunction=squared_error)GClasses::GNeuralNet
setErrorSingleOutput(double target, size_t output, TargetFunction eTargetFunction=squared_error)GClasses::GNeuralNet
setFeatureFilter(GTwoWayIncrementalTransform *pFilter)GClasses::GSupervisedLearner
setImprovementThresh(double d)GClasses::GNeuralNet [inline]
setLabelFilter(GTwoWayIncrementalTransform *pFilter)GClasses::GSupervisedLearner
setLearningRate(double d)GClasses::GNeuralNet [inline]
setMomentum(double d)GClasses::GNeuralNet [inline]
setupFilters(GMatrix &features, GMatrix &labels)GClasses::GSupervisedLearner [protected]
setUseInputBias(bool b)GClasses::GNeuralNet [inline]
setValidationPortion(double d)GClasses::GNeuralNet [inline]
setWeights(const double *pWeights)GClasses::GNeuralNet
setWindowSize(size_t n)GClasses::GNeuralNet [inline]
sign enum valueGClasses::GNeuralNet
squared_error enum valueGClasses::GNeuralNet
sumSquaredPredictionError(const double *pTarget)GClasses::GNeuralNet
supportedFeatureRange(double *pOutMin, double *pOutMax)GClasses::GNeuralNet [protected, virtual]
supportedLabelRange(double *pOutMin, double *pOutMax)GClasses::GNeuralNet [protected, virtual]
swapNodes(size_t layer, size_t a, size_t b)GClasses::GNeuralNet
TargetFunction enum nameGClasses::GNeuralNet
test()GClasses::GNeuralNet [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)GClasses::GNeuralNet [protected, virtual]
trainInner(GMatrix &features, GMatrix &labels)GClasses::GNeuralNet [protected, virtual]
trainSparse(GSparseMatrix &features, GMatrix &labels)GClasses::GNeuralNet [virtual]
trainWithValidation(GMatrix &trainFeatures, GMatrix &trainLabels, GMatrix &validateFeatures, GMatrix &validateLabels)GClasses::GNeuralNet
transduce(GMatrix &features1, GMatrix &labels1, GMatrix &features2)GClasses::GTransducer
transduceInner(GMatrix &features1, GMatrix &labels1, GMatrix &features2)GClasses::GSupervisedLearner [protected, virtual]
useInputBias()GClasses::GNeuralNet [inline]
validationSquaredError(GMatrix &features, GMatrix &labels)GClasses::GNeuralNet [protected]
weights(double *pOutWeights)GClasses::GNeuralNet
windowSize()GClasses::GNeuralNet [inline]
~GIncrementalLearner()GClasses::GIncrementalLearner [inline, virtual]
~GNeuralNet()GClasses::GNeuralNet [virtual]
~GSupervisedLearner()GClasses::GSupervisedLearner [virtual]
~GTransducer()GClasses::GTransducer [virtual]