Logo ROOT   6.21/01
Reference Guide
TMVA

The Multi Variate Analysis package.

The TMVA Multi-Variate-Analysis classes.

See:

Classes

class  TMVA::AbsoluteDeviationLossFunction
 Absolute Deviation Loss Function. More...
 
class  TMVA::AbsoluteDeviationLossFunctionBDT
 Absolute Deviation BDT Loss Function. More...
 
class  TMVA::BDTEventWrapper
 
class  TMVA::BinarySearchTree
 A simple Binary search tree including a volume search method. More...
 
class  TMVA::BinarySearchTreeNode
 Node for the BinarySearch or Decision Trees. More...
 
class  TMVA::BinaryTree
 Base class for BinarySearch and Decision Trees. More...
 
class  TMVA::CCPruner
 A helper class to prune a decision tree using the Cost Complexity method (see Classification and Regression Trees by Leo Breiman et al) More...
 
class  TMVA::CCTreeWrapper
 
class  TMVA::Classification
 Class to perform two class classification. More...
 
class  TMVA::ClassificationResult
 Class to save the results of the classifier. More...
 
class  TMVA::ClassifierFactory
 This is the MVA factory. More...
 
class  TMVA::ClassInfo
 Class that contains all the information of a class. More...
 
class  TMVA::Config
 Singleton class for global configuration settings used by TMVA. More...
 
class  TMVA::ConvergenceTest
 Check for convergence. More...
 
class  TMVA::CostComplexityPruneTool
 A class to prune a decision tree using the Cost Complexity method. More...
 
class  TMVA::CrossEntropy
 Implementation of the CrossEntropy as separation criterion. More...
 
class  TMVA::CrossValidation
 Class to perform cross validation, splitting the dataloader into folds. More...
 
class  TMVA::CrossValidationResult
 Class to save the results of cross validation, the metric for the classification ins ROC and you can ROC curves ROC integrals, ROC average and ROC standard deviation. More...
 
class  TMVA::DataInputHandler
 Class that contains all the data information. More...
 
class  TMVA::DataLoader
 
class  TMVA::DataSet
 Class that contains all the data information. More...
 
class  TMVA::DataSetFactory
 Class that contains all the data information. More...
 
class  TMVA::DataSetInfo
 Class that contains all the data information. More...
 
class  TMVA::DataSetManager
 Class that contains all the data information. More...
 
class  TMVA::DecisionTree
 Implementation of a Decision Tree. More...
 
class  TMVA::Envelope
 Abstract base class for all high level ml algorithms, you can book ml methods like BDT, MLP. More...
 
class  TMVA::Event
 
class  TMVA::ExpectedErrorPruneTool
 A helper class to prune a decision tree using the expected error (C4.5) method. More...
 
class  TMVA::Factory
 This is the main MVA steering class. More...
 
class  TMVA::FitterBase
 Base class for TMVA fitters. More...
 
class  TMVA::GeneticAlgorithm
 Base definition for genetic algorithm. More...
 
class  TMVA::GeneticFitter
 Fitter using a Genetic Algorithm. More...
 
class  TMVA::GeneticGenes
 Cut optimisation interface class for genetic algorithm. More...
 
class  TMVA::GeneticPopulation
 Population definition for genetic algorithm. More...
 
class  TMVA::GeneticRange
 Range definition for genetic algorithm. More...
 
class  TMVA::GiniIndex
 Implementation of the GiniIndex as separation criterion. More...
 
class  TMVA::GiniIndexWithLaplace
 Implementation of the GiniIndex With Laplace correction as separation criterion. More...
 
class  TMVA::HuberLossFunction
 Huber Loss Function. More...
 
class  TMVA::HuberLossFunctionBDT
 Huber BDT Loss Function. More...
 
class  TMVA::HyperParameterOptimisation
 
class  TMVA::HyperParameterOptimisationResult
 
class  TMVA::IFitterTarget
 Interface for a fitter 'target'. More...
 
class  TMVA::IMethod
 Interface for all concrete MVA method implementations. More...
 
class  TMVA::Interval
 The TMVA::Interval Class. More...
 
class  TMVA::IPruneTool
 IPruneTool - a helper interface class to prune a decision tree. More...
 
class  TMVA::IPythonInteractive
 This class is needed by JsMVA, and it's a helper class for tracking errors during the training in Jupyter notebook. More...
 
class  TMVA::KDEKernel
 KDE Kernel for "smoothing" the PDFs. More...
 
class  TMVA::LDA
 
class  TMVA::LeastSquaresLossFunction
 Least Squares Loss Function. More...
 
class  TMVA::LeastSquaresLossFunctionBDT
 Least Squares BDT Loss Function. More...
 
class  TMVA::LogInterval
 The TMVA::Interval Class. More...
 
class  TMVA::MCFitter
 Fitter using Monte Carlo sampling of parameters. More...
 
class  TMVA::MethodANNBase
 Base class for all TMVA methods using artificial neural networks. More...
 
class  TMVA::MethodBase
 Virtual base Class for all MVA method. More...
 
class  TMVA::MethodBayesClassifier
 Description of bayesian classifiers. More...
 
class  TMVA::MethodBDT
 Analysis of Boosted Decision Trees. More...
 
class  TMVA::MethodBoost
 Class for boosting a TMVA method. More...
 
class  TMVA::MethodCategory
 Class for categorizing the phase space. More...
 
class  TMVA::MethodCFMlpANN
 Interface to Clermond-Ferrand artificial neural network. More...
 
class  TMVA::MethodCFMlpANN_Utils
 Implementation of Clermond-Ferrand artificial neural network. More...
 
class  TMVA::MethodCompositeBase
 Virtual base class for combining several TMVA method. More...
 
class  TMVA::MethodCrossValidation
 
class  TMVA::MethodCuts
 Multivariate optimisation of signal efficiency for given background efficiency, applying rectangular minimum and maximum requirements. More...
 
class  TMVA::MethodDNN
 Deep Neural Network Implementation. More...
 
class  TMVA::MethodDT
 Analysis of Boosted Decision Trees. More...
 
class  TMVA::MethodFDA
 Function discriminant analysis (FDA). More...
 
class  TMVA::MethodFisher
 Fisher and Mahalanobis Discriminants (Linear Discriminant Analysis) More...
 
class  TMVA::MethodHMatrix
 H-Matrix method, which is implemented as a simple comparison of chi-squared estimators for signal and background, taking into account the linear correlations between the input variables. More...
 
class  TMVA::MethodKNN
 Analysis of k-nearest neighbor. More...
 
class  TMVA::MethodLD
 Linear Discriminant. More...
 
class  TMVA::MethodLikelihood
 Likelihood analysis ("non-parametric approach") More...
 
class  TMVA::MethodMLP
 Multilayer Perceptron class built off of MethodANNBase. More...
 
class  TMVA::MethodPDEFoam
 The PDEFoam method is an extension of the PDERS method, which divides the multi-dimensional phase space in a finite number of hyper-rectangles (cells) of constant event density. More...
 
class  TMVA::MethodPDERS
 This is a generalization of the above Likelihood methods to \( N_{var} \) dimensions, where \( N_{var} \) is the number of input variables used in the MVA. More...
 
class  TMVA::MethodRuleFit
 J Friedman's RuleFit method. More...
 
class  TMVA::MethodSVM
 SMO Platt's SVM classifier with Keerthi & Shavade improvements. More...
 
class  TMVA::MethodTMlpANN
 This is the TMVA TMultiLayerPerceptron interface class. More...
 
class  TMVA::MinuitFitter
 /Fitter using MINUIT More...
 
class  TMVA::MinuitWrapper
 Wrapper around MINUIT. More...
 
class  TMVA::MisClassificationError
 Implementation of the MisClassificationError as separation criterion. More...
 
class  TMVA::MsgLogger
 ostringstream derivative to redirect and format output More...
 
class  TMVA::Node
 Node for the BinarySearch or Decision Trees. More...
 
class  TMVA::kNN::Node< T >
 This file contains binary tree and global function template that searches tree for k-nearest neigbors. More...
 
class  TMVA::OptimizeConfigParameters
 
class  TMVA::OptionBase
 Class for TMVA-option handling. More...
 
class  TMVA::OptionMap
 class to storage options for the differents methods More...
 
class  TMVA::PDEFoam
 Implementation of PDEFoam. More...
 
class  TMVA::PDEFoamCell
 
class  TMVA::PDEFoamDecisionTree
 This PDEFoam variant acts like a decision tree and stores in every cell the discriminant. More...
 
class  TMVA::PDEFoamDecisionTreeDensity
 This is a concrete implementation of PDEFoam. More...
 
class  TMVA::PDEFoamDensityBase
 This is an abstract class, which provides an interface for a PDEFoam density estimator. More...
 
class  TMVA::PDEFoamDiscriminant
 This PDEFoam variant stores in every cell the discriminant. More...
 
class  TMVA::PDEFoamDiscriminantDensity
 This is a concrete implementation of PDEFoam. More...
 
class  TMVA::PDEFoamEvent
 This PDEFoam variant stores in every cell the sum of event weights and the sum of the squared event weights. More...
 
class  TMVA::PDEFoamEventDensity
 This is a concrete implementation of PDEFoam. More...
 
class  TMVA::PDEFoamKernelBase
 This class is the abstract kernel interface for PDEFoam. More...
 
class  TMVA::PDEFoamKernelGauss
 This PDEFoam kernel estimates a cell value for a given event by weighting all cell values with a gauss function. More...
 
class  TMVA::PDEFoamKernelLinN
 This PDEFoam kernel estimates a cell value for a given event by weighting with cell values of the nearest neighbor cells. More...
 
class  TMVA::PDEFoamKernelTrivial
 This class is a trivial PDEFoam kernel estimator. More...
 
class  TMVA::PDEFoamMultiTarget
 This PDEFoam variant is used to estimate multiple targets by creating an event density foam (PDEFoamEvent), which has dimension: More...
 
class  TMVA::PDEFoamTarget
 This PDEFoam variant stores in every cell the average target fTarget (see the Constructor) as well as the statistical error on the target fTarget. More...
 
class  TMVA::PDEFoamTargetDensity
 This is a concrete implementation of PDEFoam. More...
 
class  TMVA::PDEFoamVect
 
class  TMVA::PDF
 PDF wrapper for histograms; uses user-defined spline interpolation. More...
 
class  TMVA::QuickMVAProbEstimator
 
class  TMVA::Ranking
 Ranking for variables in method (implementation) More...
 
class  TMVA::Reader
 The Reader class serves to use the MVAs in a specific analysis context. More...
 
class  TMVA::RegressionVariance
 Calculate the "SeparationGain" for Regression analysis separation criteria used in various training algorithms. More...
 
class  TMVA::Results
 Class that is the base-class for a vector of result. More...
 
class  TMVA::ResultsClassification
 Class that is the base-class for a vector of result. More...
 
class  TMVA::ResultsMulticlass
 Class which takes the results of a multiclass classification. More...
 
class  TMVA::ResultsRegression
 Class that is the base-class for a vector of result. More...
 
class  TMVA::ROCCalc
 
class  TMVA::ROCCurve
 
class  TMVA::RootFinder
 Root finding using Brents algorithm (translated from CERNLIB function RZERO) More...
 
class  TMVA::Rule
 Implementation of a rule. More...
 
class  TMVA::RuleCut
 A class describing a 'rule cut'. More...
 
class  TMVA::RuleEnsemble
 
class  TMVA::RuleFit
 A class implementing various fits of rule ensembles. More...
 
class  TMVA::RuleFitAPI
 J Friedman's RuleFit method. More...
 
class  TMVA::RuleFitParams
 A class doing the actual fitting of a linear model using rules as base functions. More...
 
class  TMVA::SdivSqrtSplusB
 Implementation of the SdivSqrtSplusB as separation criterion. More...
 
class  TMVA::SeparationBase
 An interface to calculate the "SeparationGain" for different separation criteria used in various training algorithms. More...
 
class  TMVA::SimulatedAnnealing
 Base implementation of simulated annealing fitting procedure. More...
 
class  TMVA::SimulatedAnnealingFitter
 Fitter using a Simulated Annealing Algorithm. More...
 
class  TMVA::SVEvent
 Event class for Support Vector Machine. More...
 
class  TMVA::SVKernelFunction
 Kernel for Support Vector Machine. More...
 
class  TMVA::SVKernelMatrix
 Kernel matrix for Support Vector Machine. More...
 
class  TMVA::SVWorkingSet
 Working class for Support Vector Machine. More...
 
class  TMVA::TActivation
 Interface for TNeuron activation function classes. More...
 
class  TMVA::TActivationChooser
 Class for easily choosing activation functions. More...
 
class  TMVA::TActivationIdentity
 Identity activation function for TNeuron. More...
 
class  TMVA::TActivationRadial
 Radial basis activation function for ANN. More...
 
class  TMVA::TActivationReLU
 Rectified Linear Unit activation function for TNeuron. More...
 
class  TMVA::TActivationSigmoid
 Sigmoid activation function for TNeuron. More...
 
class  TMVA::TActivationTanh
 Tanh activation function for ANN. More...
 
class  TMVA::Timer
 Timing information for training and evaluation of MVA methods. More...
 
class  TMVA::TNeuron
 Neuron class used by TMVA artificial neural network methods. More...
 
class  TMVA::TNeuronInput
 Interface for TNeuron input calculation classes. More...
 
class  TMVA::TNeuronInputAbs
 TNeuron input calculator – calculates the sum of the absolute values of the weighted inputs. More...
 
class  TMVA::TNeuronInputChooser
 Class for easily choosing neuron input functions. More...
 
class  TMVA::TNeuronInputSqSum
 TNeuron input calculator – calculates the squared weighted sum of inputs. More...
 
class  TMVA::TNeuronInputSum
 TNeuron input calculator – calculates the weighted sum of inputs. More...
 
class  TMVA::Tools
 Global auxiliary applications and data treatment routines. More...
 
class  TMVA::TrainingHistory
 Tracking data from training. More...
 
class  TMVA::TransformationHandler
 Class that contains all the data information. More...
 
class  TMVA::TSpline1
 Linear interpolation of TGraph. More...
 
class  TMVA::TSpline2
 Quadratic interpolation of TGraph. More...
 
class  TMVA::TSynapse
 Synapse class used by TMVA artificial neural network methods. More...
 
class  TMVA::Types
 Singleton class for Global types used by TMVA. More...
 
class  TMVA::VariableDecorrTransform
 Linear interpolation class. More...
 
class  TMVA::VariableGaussTransform
 Gaussian Transformation of input variables. More...
 
class  TMVA::VariableIdentityTransform
 Linear interpolation class. More...
 
class  TMVA::VariableImportance
 
class  TMVA::VariableImportanceResult
 
class  TMVA::VariableInfo
 Class for type info of MVA input variable. More...
 
class  TMVA::VariableNormalizeTransform
 Linear interpolation class. More...
 
class  TMVA::VariablePCATransform
 Linear interpolation class. More...
 
class  TMVA::VariableRearrangeTransform
 Rearrangement of input variables. More...
 
class  TMVA::VariableTransformBase
 Linear interpolation class. More...
 
class  TMVA::Volume
 Volume for BinarySearchTree. More...