Logo ROOT   6.12/07
Reference Guide
TMVA::DNN::ClassificationSettings Member List

This is the complete list of members for TMVA::DNN::ClassificationSettings, including all inherited members.

addPoint(std::string histoName, double x)TMVA::DNN::Settingsinline
addPoint(std::string histoName, double x, double y)TMVA::DNN::Settingsinline
batchSize() constTMVA::DNN::Settingsinline
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::ClassificationSettingsinline
clear(std::string histoName)TMVA::DNN::Settingsinline
computeResult(const Net &, std::vector< double > &)TMVA::DNN::Settingsinlinevirtual
convergenceCount() constTMVA::DNN::Settingsinline
convergenceSteps() constTMVA::DNN::Settingsinline
count_dETMVA::DNN::Settings
count_ETMVA::DNN::Settings
count_mb_dETMVA::DNN::Settings
count_mb_ETMVA::DNN::Settings
create(std::string histoName, int bins, double min, double max)TMVA::DNN::Settingsinline
create(std::string histoName, int bins, double min, double max, int bins2, double min2, double max2)TMVA::DNN::Settingsinline
cycle(double progress, TString text)TMVA::DNN::Settingsinlinevirtual
drawSample(const std::vector< double > &, const std::vector< double > &, const std::vector< double > &, double)TMVA::DNN::Settingsinlinevirtual
dropFractions() constTMVA::DNN::Settingsinline
dropRepetitions() constTMVA::DNN::Settingsinline
endTestCycle()TMVA::DNN::ClassificationSettingsvirtual
endTrainCycle(double)TMVA::DNN::ClassificationSettingsvirtual
exists(std::string histoName)TMVA::DNN::Settingsinline
factorWeightDecay() constTMVA::DNN::Settingsinline
fLearningRateTMVA::DNN::Settings
fMinimizerTypeTMVA::DNN::Settings
fMomentumTMVA::DNN::Settings
fMonitoringTMVA::DNN::Settingsprotected
fRepetitionsTMVA::DNN::Settings
hasConverged(double testError)TMVA::DNN::Settingsvirtual
learningRate() constTMVA::DNN::Settingsinline
m_amsTMVA::DNN::ClassificationSettings
m_batchSizeTMVA::DNN::Settings
m_convergenceCountTMVA::DNN::Settings
m_convergenceStepsTMVA::DNN::Settings
m_cutValueTMVA::DNN::ClassificationSettings
m_dropOutTMVA::DNN::Settings
m_dropRepetitionsTMVA::DNN::Settings
m_factorWeightDecayTMVA::DNN::Settings
m_fileNameNetConfigTMVA::DNN::ClassificationSettings
m_fileNameResultTMVA::DNN::ClassificationSettings
m_inputTMVA::DNN::ClassificationSettings
m_maxConvergenceCountTMVA::DNN::Settings
m_maxProgressTMVA::DNN::Settings
m_minErrorTMVA::DNN::Settings
m_minProgressTMVA::DNN::Settings
m_outputTMVA::DNN::ClassificationSettings
m_pResultPatternContainerTMVA::DNN::ClassificationSettings
m_regularizationTMVA::DNN::Settings
m_scaleToNumEventsTMVA::DNN::ClassificationSettings
m_significancesTMVA::DNN::ClassificationSettings
m_sumOfBkgWeightsTMVA::DNN::ClassificationSettings
m_sumOfSigWeightsTMVA::DNN::ClassificationSettings
m_targetsTMVA::DNN::ClassificationSettings
m_testRepetitionsTMVA::DNN::Settings
m_timerTMVA::DNN::Settings
m_useMultithreadingTMVA::DNN::Settingsprotected
m_weightsTMVA::DNN::ClassificationSettings
maxConvergenceCount() constTMVA::DNN::Settingsinline
minError() constTMVA::DNN::Settingsinline
minimizerType() constTMVA::DNN::Settingsinline
momentum() constTMVA::DNN::Settingsinline
pads(int numPads)TMVA::DNN::Settingsinline
plot(std::string histoName, std::string options, int pad, EColor color)TMVA::DNN::Settingsinline
regularization() constTMVA::DNN::Settingsinline
repetitions() constTMVA::DNN::Settingsinline
setDropOut(Iterator begin, Iterator end, size_t _dropRepetitions)TMVA::DNN::Settingsinline
setMonitoring(std::shared_ptr< Monitoring > ptrMonitoring)TMVA::DNN::Settingsinline
setProgressLimits(double minProgress=0, double maxProgress=100)TMVA::DNN::Settingsinlinevirtual
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()TMVA::DNN::ClassificationSettingsvirtual
startTrainCycle()TMVA::DNN::ClassificationSettingsvirtual
startTraining()TMVA::DNN::Settingsinlinevirtual
testIteration()TMVA::DNN::ClassificationSettingsinlinevirtual
testRepetitions() constTMVA::DNN::Settingsinline
testSample(double error, double output, double target, double weight)TMVA::DNN::ClassificationSettingsvirtual
useMultithreading() constTMVA::DNN::Settingsinline
~ClassificationSettings()TMVA::DNN::ClassificationSettingsinlinevirtual
~Settings()TMVA::DNN::Settingsvirtual