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TMVA::DNN::TGradientDescent< Architecture_t > Member List

This is the complete list of members for TMVA::DNN::TGradientDescent< Architecture_t >, including all inherited members.

fBatchSizeTMVA::DNN::TGradientDescent< Architecture_t >private
fConvergenceCountTMVA::DNN::TGradientDescent< Architecture_t >private
fConvergenceStepsTMVA::DNN::TGradientDescent< Architecture_t >private
fLearningRateTMVA::DNN::TGradientDescent< Architecture_t >private
fMinimumErrorTMVA::DNN::TGradientDescent< Architecture_t >private
fStepCountTMVA::DNN::TGradientDescent< Architecture_t >private
fTestErrorTMVA::DNN::TGradientDescent< Architecture_t >private
fTestIntervalTMVA::DNN::TGradientDescent< Architecture_t >private
fTrainingErrorTMVA::DNN::TGradientDescent< Architecture_t >private
GetConvergenceCount() constTMVA::DNN::TGradientDescent< Architecture_t >inline
GetConvergenceSteps() constTMVA::DNN::TGradientDescent< Architecture_t >inline
GetTestError() constTMVA::DNN::TGradientDescent< Architecture_t >inline
GetTestInterval() constTMVA::DNN::TGradientDescent< Architecture_t >inline
GetTrainingError() constTMVA::DNN::TGradientDescent< Architecture_t >inline
HasConverged()TMVA::DNN::TGradientDescent< Architecture_t >inline
HasConverged(Scalar_t testError)TMVA::DNN::TGradientDescent< Architecture_t >inline
Matrix_t typedefTMVA::DNN::TGradientDescent< Architecture_t >
Reset()TMVA::DNN::TGradientDescent< Architecture_t >inline
Scalar_t typedefTMVA::DNN::TGradientDescent< Architecture_t >
SetBatchSize(Scalar_t rate)TMVA::DNN::TGradientDescent< Architecture_t >inline
SetConvergenceSteps(size_t steps)TMVA::DNN::TGradientDescent< Architecture_t >inline
SetLearningRate(Scalar_t rate)TMVA::DNN::TGradientDescent< Architecture_t >inline
SetTestInterval(size_t interval)TMVA::DNN::TGradientDescent< Architecture_t >inline
Step(Net_t &net, Matrix_t &input, const Matrix_t &output, const Matrix_t &weights)TMVA::DNN::TGradientDescent< Architecture_t >inline
Step(Net_t &master, std::vector< Net_t > &nets, std::vector< TBatch< Architecture_t > > &batches)TMVA::DNN::TGradientDescent< Architecture_t >inline
StepLoss(Net_t &net, Matrix_t &input, const Matrix_t &output, const Matrix_t &weights)TMVA::DNN::TGradientDescent< Architecture_t >
StepLoss(Net_t &net, Matrix_t &input, const Matrix_t &output, const Matrix_t &weights) -> Scalar_tTMVA::DNN::TGradientDescent< Architecture_t >inline
StepMomentum(Net_t &master, std::vector< Net_t > &nets, std::vector< TBatch< Architecture_t > > &batches, Scalar_t momentum)TMVA::DNN::TGradientDescent< Architecture_t >inline
StepNesterov(Net_t &master, std::vector< Net_t > &nets, std::vector< TBatch< Architecture_t > > &batches, Scalar_t momentum)TMVA::DNN::TGradientDescent< Architecture_t >inline
StepReducedWeights(Net_t &net, Matrix_t &input, const Matrix_t &output)TMVA::DNN::TGradientDescent< Architecture_t >inline
StepReducedWeightsLoss(Net_t &net, Matrix_t &input, const Matrix_t &output, const Matrix_t &weights)TMVA::DNN::TGradientDescent< Architecture_t >
StepReducedWeightsLoss(Net_t &net, Matrix_t &input, const Matrix_t &output, const Matrix_t &weights) -> Scalar_tTMVA::DNN::TGradientDescent< Architecture_t >inline
TGradientDescent()TMVA::DNN::TGradientDescent< Architecture_t >
TGradientDescent(Scalar_t learningRate, size_t convergenceSteps, size_t testInterval)TMVA::DNN::TGradientDescent< Architecture_t >
Train(const Data_t &TrainingDataIn, size_t nTrainingSamples, const Data_t &TestDataIn, size_t nTestSamples, Net_t &net, size_t nThreads=1)TMVA::DNN::TGradientDescent< Architecture_t >
Train(const Data_t &trainingData, size_t nTrainingSamples, const Data_t &testData, size_t nTestSamples, Net_t &net, size_t nThreads) -> Scalar_tTMVA::DNN::TGradientDescent< Architecture_t >
TrainMomentum(const Data_t &TrainingDataIn, size_t nTrainingSamples, const Data_t &TestDataIn, size_t nTestSamples, Net_t &net, Scalar_t momentum, size_t nThreads=1)TMVA::DNN::TGradientDescent< Architecture_t >
TrainMomentum(const Data_t &trainingData, size_t nTrainingSamples, const Data_t &testData, size_t nTestSamples, Net_t &net, Scalar_t momentum, size_t nThreads) -> Scalar_tTMVA::DNN::TGradientDescent< Architecture_t >