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TMVA
Index of TMVA
This directory contains the
TMVA
Multi-Variate-Analysis classes.
See:
The full description of the Multi Variate Analysis package
The TMVA Users Guide
The TMVA Options Reference
Class Index
Jump to
T
TMVA:
TMVA::I
TMVA::M
TMVA::Me
TMVA::MethodS
TMVA::P
TMVA::PDEFoamK
TMVA::R
TMVA::T
TMVA::TS
TMVA::V
TMVA
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::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::DecisionTree
implementation of a Decision Tree
TMVA::DecisionTreeNode
Node for the Decision Tree
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::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::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::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::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::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::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::Types
TMVA::VariableDecorrTransform
Variable transformation: decorrelation
TMVA::VariableGaussTransform
Variable transformation: Gauss transformation
TMVA::VariableIdentityTransform
Variable transformation: identity
TMVA::VariableNormalizeTransform
Variable transformation: normalization
TMVA::VariablePCATransform
Variable transformation: Principal Value Composition
TMVA::VariableRearrangeTransform
Variable transformation: normalization
TMVA::VariableTransformBase
Base class for variable transformations