| addPoint(std::string histoName, double x) | TMVA::DNN::Settings | inline |
| addPoint(std::string histoName, double x, double y) | TMVA::DNN::Settings | inline |
| batchSize() const | TMVA::DNN::Settings | inline |
| ClassificationSettings(TString name, size_t _convergenceSteps=15, size_t _batchSize=10, size_t _testRepetitions=7, double _factorWeightDecay=1e-5, EnumRegularization _regularization=EnumRegularization::NONE, size_t _scaleToNumEvents=0, MinimizerType _eMinimizerType=MinimizerType::fSteepest, double _learningRate=1e-5, double _momentum=0.3, int _repetitions=3, bool _useMultithreading=true) | TMVA::DNN::ClassificationSettings | inline |
| clear(std::string histoName) | TMVA::DNN::Settings | inline |
| computeResult(const Net &, std::vector< double > &) | TMVA::DNN::Settings | inlinevirtual |
| convergenceCount() const | TMVA::DNN::Settings | inline |
| convergenceSteps() const | TMVA::DNN::Settings | inline |
| count_dE | TMVA::DNN::Settings | |
| count_E | TMVA::DNN::Settings | |
| count_mb_dE | TMVA::DNN::Settings | |
| count_mb_E | TMVA::DNN::Settings | |
| create(std::string histoName, int bins, double min, double max) | TMVA::DNN::Settings | inline |
| create(std::string histoName, int bins, double min, double max, int bins2, double min2, double max2) | TMVA::DNN::Settings | inline |
| cycle(double progress, TString text) | TMVA::DNN::Settings | inlinevirtual |
| drawSample(const std::vector< double > &, const std::vector< double > &, const std::vector< double > &, double) | TMVA::DNN::Settings | inlinevirtual |
| dropFractions() const | TMVA::DNN::Settings | inline |
| dropRepetitions() const | TMVA::DNN::Settings | inline |
| endTestCycle() override | TMVA::DNN::ClassificationSettings | virtual |
| endTrainCycle(double) override | TMVA::DNN::ClassificationSettings | virtual |
| exists(std::string histoName) | TMVA::DNN::Settings | inline |
| factorWeightDecay() const | TMVA::DNN::Settings | inline |
| fLearningRate | TMVA::DNN::Settings | |
| fMinimizerType | TMVA::DNN::Settings | |
| fMomentum | TMVA::DNN::Settings | |
| fMonitoring | TMVA::DNN::Settings | protected |
| fRepetitions | TMVA::DNN::Settings | |
| hasConverged(double testError) | TMVA::DNN::Settings | virtual |
| learningRate() const | TMVA::DNN::Settings | inline |
| m_ams | TMVA::DNN::ClassificationSettings | |
| m_batchSize | TMVA::DNN::Settings | |
| m_convergenceCount | TMVA::DNN::Settings | |
| m_convergenceSteps | TMVA::DNN::Settings | |
| m_cutValue | TMVA::DNN::ClassificationSettings | |
| m_dropOut | TMVA::DNN::Settings | |
| m_dropRepetitions | TMVA::DNN::Settings | |
| m_factorWeightDecay | TMVA::DNN::Settings | |
| m_fileNameNetConfig | TMVA::DNN::ClassificationSettings | |
| m_fileNameResult | TMVA::DNN::ClassificationSettings | |
| m_input | TMVA::DNN::ClassificationSettings | |
| m_maxConvergenceCount | TMVA::DNN::Settings | |
| m_maxProgress | TMVA::DNN::Settings | |
| m_minError | TMVA::DNN::Settings | |
| m_minProgress | TMVA::DNN::Settings | |
| m_output | TMVA::DNN::ClassificationSettings | |
| m_pResultPatternContainer | TMVA::DNN::ClassificationSettings | |
| m_regularization | TMVA::DNN::Settings | |
| m_scaleToNumEvents | TMVA::DNN::ClassificationSettings | |
| m_significances | TMVA::DNN::ClassificationSettings | |
| m_sumOfBkgWeights | TMVA::DNN::ClassificationSettings | |
| m_sumOfSigWeights | TMVA::DNN::ClassificationSettings | |
| m_targets | TMVA::DNN::ClassificationSettings | |
| m_testRepetitions | TMVA::DNN::Settings | |
| m_timer | TMVA::DNN::Settings | |
| m_useMultithreading | TMVA::DNN::Settings | protected |
| m_weights | TMVA::DNN::ClassificationSettings | |
| maxConvergenceCount() const | TMVA::DNN::Settings | inline |
| minError() const | TMVA::DNN::Settings | inline |
| minimizerType() const | TMVA::DNN::Settings | inline |
| momentum() const | TMVA::DNN::Settings | inline |
| pads(int numPads) | TMVA::DNN::Settings | inline |
| plot(std::string histoName, std::string options, int pad, EColor color) | TMVA::DNN::Settings | inline |
| regularization() const | TMVA::DNN::Settings | inline |
| repetitions() const | TMVA::DNN::Settings | inline |
| setDropOut(Iterator begin, Iterator end, size_t _dropRepetitions) | TMVA::DNN::Settings | inline |
| setMonitoring(std::shared_ptr< Monitoring > ptrMonitoring) | TMVA::DNN::Settings | inline |
| setProgressLimits(double minProgress=0, double maxProgress=100) | TMVA::DNN::Settings | inlinevirtual |
| setResultComputation(std::string _fileNameNetConfig, std::string _fileNameResult, std::vector< Pattern > *_resultPatternContainer) | TMVA::DNN::ClassificationSettings | |
| Settings(TString name, size_t _convergenceSteps=15, size_t _batchSize=10, size_t _testRepetitions=7, double _factorWeightDecay=1e-5, TMVA::DNN::EnumRegularization _regularization=TMVA::DNN::EnumRegularization::NONE, MinimizerType _eMinimizerType=MinimizerType::fSteepest, double _learningRate=1e-5, double _momentum=0.3, int _repetitions=3, bool _multithreading=true) | TMVA::DNN::Settings | |
| setWeightSums(double sumOfSigWeights, double sumOfBkgWeights) | TMVA::DNN::ClassificationSettings | |
| startTestCycle() override | TMVA::DNN::ClassificationSettings | virtual |
| startTrainCycle() override | TMVA::DNN::ClassificationSettings | virtual |
| startTraining() | TMVA::DNN::Settings | inlinevirtual |
| testIteration() override | TMVA::DNN::ClassificationSettings | inlinevirtual |
| testRepetitions() const | TMVA::DNN::Settings | inline |
| testSample(double error, double output, double target, double weight) override | TMVA::DNN::ClassificationSettings | virtual |
| useMultithreading() const | TMVA::DNN::Settings | inline |
| ~ClassificationSettings() | TMVA::DNN::ClassificationSettings | inlinevirtual |
| ~Settings() | TMVA::DNN::Settings | virtual |
