Ejemplo n.º 1
0
void TMVACrossValidation()
{
   // This loads the library
   TMVA::Tools::Instance();

   // Load data
   TFile *input(0);
   TString fname = "./tmva_class_example.root";
   if (!gSystem->AccessPathName( fname )) {
      input = TFile::Open( fname ); // check if file in local directory exists
   }
   else {
      TFile::SetCacheFileDir(".");
      input = TFile::Open("http://root.cern.ch/files/tmva_class_example.root", "CACHEREAD");
   }
   if (!input) {
      std::cout << "ERROR: could not open data file" << std::endl;
      exit(1);
   }

   TTree* signalTree = (TTree*)input->Get("TreeS");
   TTree* background = (TTree*)input->Get("TreeB");

   // Setup dataloader
   TMVA::DataLoader* dataloader = new TMVA::DataLoader("dataset");

   dataloader->AddSignalTree(signalTree);
   dataloader->AddBackgroundTree(background);

   dataloader->AddVariable("var1");
   dataloader->AddVariable("var2");
   dataloader->AddVariable("var3");
   dataloader->AddVariable("var4");

   dataloader->PrepareTrainingAndTestTree("", "SplitMode=Random:NormMode=NumEvents:!V");

   // Setup cross-validation with Fisher method
   TMVA::CrossValidation cv(dataloader);
   cv.BookMethod(TMVA::Types::kFisher, "Fisher", "!H:!V:Fisher");

   // Run cross-validation and print results
   cv.Evaluate();
   TMVA::CrossValidationResult results = cv.GetResults();
   results.Print();
}
Ejemplo n.º 2
0
void TMVACrossValidation()
{
   // This loads the library
   TMVA::Tools::Instance();

   // Load data
   TString fname = "./tmva_class_example.root";
   if (gSystem->AccessPathName(fname))
      gSystem->Exec("curl -O http://root.cern.ch/files/tmva_class_example.root");
   TFile *input = TFile::Open(fname);

   TTree* signalTree = (TTree*)input->Get("TreeS");
   TTree* background = (TTree*)input->Get("TreeB");

   // Setup dataloader
   TMVA::DataLoader* dataloader = new TMVA::DataLoader("dataset");

   dataloader->AddSignalTree(signalTree);
   dataloader->AddBackgroundTree(background);

   dataloader->AddVariable("var1");
   dataloader->AddVariable("var2");
   dataloader->AddVariable("var3");
   dataloader->AddVariable("var4");

   dataloader->PrepareTrainingAndTestTree("", "SplitMode=Random:NormMode=NumEvents:!V");

   // Setup cross-validation with Fisher method
   TMVA::CrossValidation cv(dataloader);
   cv.BookMethod(TMVA::Types::kFisher, "Fisher", "!H:!V:Fisher");

   // Run cross-validation and print results
   cv.Evaluate();
   TMVA::CrossValidationResult results = cv.GetResults();
   results.Print();
}