void train()
{
TFile* outputFile = TFile::Open("output.root","RECREATE");
TMVA::Factory *factory = new TMVA::Factory( "TMVAClassification", outputFile,
"!V:Color:DrawProgressBar:Transformations=I:AnalysisType=Classification");
TFile* inputFile = new TFile("sig_train.root");
TFile* inputFilebkg = new TFile("bkg_train.root");
TTree* sig = (TTree*)inputFile->Get("b0");
TTree* bkg = (TTree*)inputFilebkg->Get("b0");
double sigWeight = 1.0; double bkgWeight = 1.0;
TMVA::DataLoader *dataloader = new TMVA::DataLoader("dataset");
dataloader->AddSignalTree(sig, sigWeight);
dataloader->AddBackgroundTree(bkg, bkgWeight);
dataloader->AddVariable( "useCMSFrame__bocosTheta__bc", 'F' );
dataloader->AddVariable( "cosTBTO", 'F' );
dataloader->AddVariable( "cosTBz", 'F' );
dataloader->AddVariable( "KSFWVariables__boet__bc",      'F' );
//dataloader->AddVariable( "KSFWVariables__bohso00__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso02__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso04__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso10__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso12__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso14__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso20__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso22__bc",  'F');
dataloader->AddVariable( "KSFWVariables__bohso24__bc",  'F');
//dataloader->AddVariable( "KSFWVariables__bohoo0__bc",   'F');
//dataloader->AddVariable( "KSFWVariables__bohoo1__bc",   'F');
//dataloader->AddVariable( "KSFWVariables__bohoo2__bc",   'F');
//dataloader->AddVariable( "KSFWVariables__bohoo3__bc",   'F');
//dataloader->AddVariable( "KSFWVariables__bohoo4__bc",   'F');

TCut mycut = "";
dataloader->PrepareTrainingAndTestTree(mycut,"nTrain_Signal=0:nTrain_Background=0:SplitMode=Random:NormMode=NumEvents:!V");
factory->BookMethod(dataloader, TMVA::Types::kBDT, "BDT", "!H:!V:CreateMVAPdfs:BoostType=Grad:BaggedSampleFraction=0.5:NTrees=150:Shrinkage=0.2:MaxDepth=3:IgnoreNegWeightsInTraining");
factory->BookMethod(dataloader, TMVA::Types::kFisher, "Fisher", "!H:!V:Fisher");
factory->TrainAllMethods(); // Train MVAs using training events
factory->TestAllMethods(); // Evaluate all MVAs using test events
// ----- Evaluate and compare performance of all configured MVAs
factory->EvaluateAllMethods();
outputFile->Close();
delete factory; delete dataloader;

// Open TMVA Gui
//TMVASYS="$ROOTSYS" root -e "TMVA::TMVAGui(\"output.root\")"
}