Examples showing how to use Machine Learning from ROOT.
Modules | |
Envelope Tutorials | |
TMVA Keras tutorials | |
Example code which illustrates how to use keras with the python interface of TMVA. | |
TMVA PyTorch tutorials | |
Example code which illustrates how to use pytorch with the python interface of TMVA. | |
Files | |
file | createData.C |
Plot the variables. | |
file | tmva001_RTensor.C |
This tutorial illustrates the basic features of the RTensor class, RTensor is a std::vector-like container with additional shape information. | |
file | tmva002_RDataFrameAsTensor.C |
This tutorial shows how the content of an RDataFrame can be converted to an RTensor object. | |
file | tmva003_RReader.C |
This tutorial shows how to apply with the modern interfaces models saved in TMVA XML files. | |
file | tmva004_RStandardScaler.C |
This tutorial illustrates the usage of the standard scaler as preprocessing method. | |
file | tmva103_Application.C |
This tutorial illustrates how you can conveniently apply BDTs in C++ using the fast tree inference engine offered by TMVA. | |
file | TMVA_CNN_Classification.C |
TMVA Classification Example Using a Convolutional Neural Network | |
file | TMVA_Higgs_Classification.C |
Classification example of TMVA based on public Higgs UCI dataset | |
file | TMVA_RNN_Classification.C |
TMVA Classification Example Using a Recurrent Neural Network | |
file | TMVA_SOFIE_Keras.C |
This macro provides a simple example for the parsing of Keras .h5 file into RModel object and further generating the .hxx header files for inference. | |
file | TMVA_SOFIE_Keras_HiggsModel.C |
This macro run the SOFIE parser on the Keras model obtaining running TMVA_Higgs_Classification.C You need to run that macro before this one | |
file | TMVA_SOFIE_ONNX.C |
This macro provides a simple example for the parsing of ONNX files into RModel object and further generating the .hxx header files for inference. | |
file | TMVA_SOFIE_PyTorch.C |
This macro provides a simple example for the parsing of PyTorch .pt file into RModel object and further generating the .hxx header files for inference. | |
file | TMVA_SOFIE_RDataFrame.C |
This macro provides an example of using a trained model with Keras and make inference using SOFIE and RDataFrame This macro uses as input a Keras model generated with the TMVA_Higgs_Classification.C tutorial You need to run that macro before to generate the trained Keras model Then you need to run the macro TMVA_SOFIE_Keras_HiggsModel.C to generate the corresponding header file using SOFIE. | |
file | TMVA_SOFIE_RDataFrame_JIT.C |
This macro provides an example of using a trained model with Keras and make inference using SOFIE and RDataFrame This macro uses as input a Keras model generated with the TMVA_Higgs_Classification.C tutorial You need to run that macro before this one. | |
file | TMVA_SOFIE_RSofieReader.C |
This macro provides an example of using a trained model with Keras and make inference using SOFIE with the RSofieReader class This macro uses as input a Keras model generated with the TMVA_Higgs_Classification.C tutorial You need to run that macro before to generate the trained Keras model | |
file | TMVAClassification.C |
This macro provides examples for the training and testing of the TMVA classifiers. | |
file | TMVAClassificationApplication.C |
This macro provides a simple example on how to use the trained classifiers within an analysis module | |
file | TMVAClassificationCategory.C |
This macro provides examples for the training and testing of the TMVA classifiers in categorisation mode. | |
file | TMVAClassificationCategoryApplication.C |
This macro provides a simple example on how to use the trained classifiers (with categories) within an analysis module | |
file | TMVACrossValidation.C |
This macro provides an example of how to use TMVA for k-folds cross evaluation. | |
file | TMVACrossValidationApplication.C |
This macro provides an example of how to use TMVA for k-folds cross evaluation in application. | |
file | TMVACrossValidationRegression.C |
This macro provides an example of how to use TMVA for k-folds cross evaluation. | |
file | TMVAGAexample.C |
This executable gives an example of a very simple use of the genetic algorithm of TMVA | |
file | TMVAGAexample2.C |
This executable gives an example of a very simple use of the genetic algorithm of TMVA. | |
file | TMVAMinimalClassification.C |
Minimal self-contained example for setting up TMVA with binary classification. | |
file | TMVAMulticlass.C |
This macro provides a simple example for the training and testing of the TMVA multiclass classification | |
file | TMVAMulticlassApplication.C |
This macro provides a simple example on how to use the trained multiclass classifiers within an analysis module | |
file | TMVAMultipleBackgroundExample.C |
This example shows the training of signal with three different backgrounds Then in the application a tree is created with all signal and background events where the true class ID and the three classifier outputs are added finally with the application tree, the significance is maximized with the help of the TMVA genetic algorithm. | |
file | TMVARegression.C |
This macro provides examples for the training and testing of the TMVA classifiers. | |
file | TMVARegressionApplication.C |
This macro provides a simple example on how to use the trained regression MVAs within an analysis module | |