Index of TMVA

Class Index

• ROOT::Math::Factory
• ROOT::Math::RootFinder
• TMVA::BDTEventWrapper
• TMVA::BinarySearchTree Binary search tree including volume search method
• TMVA::BinarySearchTreeNode Node for the BinarySearchTree
• TMVA::BinaryTree Base class for BinarySearch and Decision Trees
• TMVA::CCPruner
• TMVA::CCTreeWrapper
• TMVA::ClassInfo
• TMVA::Config Singleton class for global configuration settings
• TMVA::Config::IONames
• TMVA::Config::VariablePlotting
• TMVA::Configurable Virtual base class for all TMVA method
• TMVA::CostComplexityPruneTool
• TMVA::CrossEntropy Implementation of the CrossEntropy as separation criterion
• TMVA::CrossValidation
• TMVA::DataInputHandler
• TMVA::DataSet
• TMVA::DataSetFactory
• TMVA::DataSetInfo
• TMVA::DataSetManager
• TMVA::DecisionTree implementation of a Decision Tree
• TMVA::DecisionTreeNode Node for the Decision Tree
• TMVA::Envelope
• TMVA::Event
• TMVA::Factory The factory creates all MVA methods, and performs their training and testing
• TMVA::FitterBase Baseclass for fitters
• TMVA::GeneticAlgorithm Genetic algorithm controller
• TMVA::GeneticFitter Fitter using a Genetic Algorithm
• TMVA::GeneticGenes Genes definition for genetic algorithm
• TMVA::GeneticPopulation Population definition for genetic algorithm
• TMVA::GeneticRange Range definition for genetic algorithm
• TMVA::GiniIndex Implementation of the GiniIndex as separation criterion
• TMVA::GiniIndexWithLaplace Implementation of the GiniIndexWithLaplace as separation criterion
• TMVA::HyperParameterOptimisation
• TMVA::IFitterTarget base class for a fitter "target"
• TMVA::IMethod Method Interface
• TMVA::Interval Interval definition, continous and discrete
• TMVA::KDEKernel Kernel density estimator for PDF smoothing
• TMVA::LogInterval Interval definition, continous and discrete
• TMVA::MCFitter Fitter using Monte Carlo sampling of parameters
• TMVA::MethodANNBase Base class for TMVA ANNs
• TMVA::MethodBDT Analysis of Boosted Decision Trees
• TMVA::MethodBase Virtual base class for all TMVA method
• TMVA::MethodBayesClassifier Friedman's BayesClassifier method
• TMVA::MethodBoost
• TMVA::MethodCFMlpANN Interface for Clermond-Ferrand artificial neural network
• TMVA::MethodCFMlpANN_Utils Implementation of Clermond-Ferrand artificial neural network
• TMVA::MethodCategory
• TMVA::MethodCompositeBase
• TMVA::MethodCuts Multivariate optimisation of signal efficiency
• TMVA::MethodDNN neural network
• TMVA::MethodDT Analysis of Decision Trees
• TMVA::MethodFDA Function Discriminant Analysis
• TMVA::MethodFisher Analysis of Fisher discriminant (Fisher or Mahalanobis approach)
• TMVA::MethodHMatrix H-Matrix method, a simple comparison of chi-squared estimators for signal and background
• TMVA::MethodKNN k Nearest Neighbour classifier
• TMVA::MethodLD Linear discriminant analysis
• TMVA::MethodLikelihood Likelihood analysis ("non-parametric approach")
• TMVA::MethodMLP Multi-layer perceptron implemented specifically for TMVA
• TMVA::MethodPDEFoam Multi-dimensional probability density estimator using TFoam (PDE-Foam)
• TMVA::MethodPDERS Multi-dimensional probability density estimator range search (PDERS) method
• TMVA::MethodRuleFit Friedman's RuleFit method
• TMVA::MethodSVM Support Vector Machine
• TMVA::MethodTMlpANN Implementation of interface for TMultiLayerPerceptron
• TMVA::MinuitFitter Fitter using a Genetic Algorithm
• TMVA::MinuitWrapper Wrapper around TMinuit
• TMVA::MisClassificationError Implementation of the MisClassificationError as separation criterion
• TMVA::MsgLogger Ostringstream derivative to redirect and format logging output
• TMVA::Node Node for the BinarySearch or Decision Trees
• TMVA::OptimizeConfigParameters Interface to different separation critiera used in training algorithms
• TMVA::OptionBase
• TMVA::OptionMap
• TMVA::PDEFoam Tree of PDEFoamCells
• TMVA::PDEFoamCell Single cell of FOAM
• TMVA::PDEFoamDecisionTree Decision tree like PDEFoam
• TMVA::PDEFoamDecisionTreeDensity Class for decision tree like PDEFoam density
• TMVA::PDEFoamDensityBase PDEFoam event density interface
• TMVA::PDEFoamDiscriminant Tree of PDEFoamCells
• TMVA::PDEFoamDiscriminantDensity Class for Discriminant density
• TMVA::PDEFoamEvent Tree of PDEFoamCells
• TMVA::PDEFoamEventDensity Class for Event density
• TMVA::PDEFoamKernelBase PDEFoam kernel interface
• TMVA::PDEFoamKernelGauss Gaussian PDEFoam kernel estimator
• TMVA::PDEFoamKernelLinN next neighbor PDEFoam kernel estimator
• TMVA::PDEFoamKernelTrivial trivial PDEFoam kernel estimator
• TMVA::PDEFoamMultiTarget Tree of PDEFoamCells
• TMVA::PDEFoamTarget Tree of PDEFoamCells
• TMVA::PDEFoamTargetDensity Class for Target density
• TMVA::PDEFoamVect n-dimensional vector with dynamical allocation
• TMVA::PDF PDF wrapper for histograms
• TMVA::QuickMVAProbEstimator Interface to different separation critiera used in training algorithms
• TMVA::ROCCalc
• TMVA::ROCCurve
• TMVA::Ranking Method-specific ranking for input variables
• TMVA::Reader Interpret the trained MVAs in an analysis context
• TMVA::RegressionVariance Interface to different separation critiera used in training algorithms
• TMVA::Results
• TMVA::ResultsClassification
• TMVA::ResultsMulticlass
• TMVA::ResultsRegression
• TMVA::RootFinder Root finding using Brents algorithm
• TMVA::RuleFit Calculations for Friedman's RuleFit method
• TMVA::RuleFitAPI Friedman's RuleFit method
• TMVA::SVEvent Event for SVM
• TMVA::SdivSqrtSplusB Implementation of the SdivSqrtSplusB as separation criterion
• TMVA::SeparationBase Interface to different separation critiera used in training algorithms
• TMVA::SimulatedAnnealing Base class for Simulated Annealing fitting
• TMVA::SimulatedAnnealingFitter Fitter using a Simulated Annealing Algorithm
• TMVA::TActivation Interface for TNeuron activation function classes
• TMVA::TActivationChooser Class for choosing activation functions
• TMVA::TActivationIdentity Identity activation function for TNeuron
• TMVA::TActivationRadial Radial basis activation function for TNeuron
• TMVA::TActivationReLU Tanh sigmoid activation function for TNeuron
• TMVA::TActivationSigmoid Sigmoid activation function for TNeuron
• TMVA::TActivationTanh Tanh sigmoid activation function for TNeuron
• TMVA::TNeuron Neuron class used by MethodANNBase derivative ANNs
• TMVA::TNeuronInput Interface for TNeuron input calculation classes
• TMVA::TNeuronInputAbs Calculates the sum of the absolute values of the weighted inputs
• TMVA::TNeuronInputChooser Class for choosing neuron input functions
• TMVA::TNeuronInputSqSum Calculates square of weighted sum of neuron inputs
• TMVA::TNeuronInputSum Calculates weighted sum of neuron inputs
• TMVA::TSpline1 Linear interpolation class
• TMVA::TSpline2 Quadratic interpolation class (using quadrax)
• TMVA::TSynapse Synapse class used by MethodANNBase and derivatives
• TMVA::Timer Timing information for training and evaluation of MVA methods
• TMVA::Tools
• TMVA::TreeInfo
• TMVA::Types
• TMVA::VariableDecorrTransform Variable transformation: decorrelation
• TMVA::VariableGaussTransform Variable transformation: Gauss transformation
• TMVA::VariableIdentityTransform Variable transformation: identity
• TMVA::VariableImportance
• TMVA::VariableInfo
• TMVA::VariableNormalizeTransform Variable transformation: normalization
• TMVA::VariablePCATransform Variable transformation: Principal Value Composition
• TMVA::VariableRearrangeTransform Variable transformation: normalization
• TMVA::VariableTransformBase Base class for variable transformations
• TMVA::kNN::Event
• TNeuron Neuron for MultiLayerPerceptrons
• TSynapse simple weighted bidirectionnal connection between 2 neurons