54 for (
Int_t n = 0;
n < nPoints; ++
n) {
55 x = rng.Rndm() * scale;
56 y = offset + rng.Rndm() * scale;
73void TMVAMinimalClassification()
75 TString outputFilename =
"out.root";
76 TFile *outFile =
new TFile(outputFilename,
"RECREATE");
79 TTree *signalTree = genTree(1000, 0.0, 2.0, 100);
80 TTree *backgroundTree = genTree(1000, 1.0, 2.0, 101);
82 TString factoryOptions =
"AnalysisType=Classification";
89 dataloader.AddVariable(
"y",
'D');
91 dataloader.AddSignalTree(signalTree, 1.0);
92 dataloader.AddBackgroundTree(backgroundTree, 1.0);
95 TCut backgroundCut =
"";
96 TString datasetOptions =
"SplitMode=Random";
97 dataloader.PrepareTrainingAndTestTree(signalCut, backgroundCut, datasetOptions);
104 factory.TrainAllMethods();
105 factory.TestAllMethods();
106 factory.EvaluateAllMethods();
113 delete backgroundTree;
A specialized string object used for TTree selections.
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format.
virtual void Close(Option_t *option="")
Close a file.
void AddVariable(const TString &expression, const TString &title, const TString &unit, char type='F', Double_t min=0, Double_t max=0)
user inserts discriminating variable in data set info
This is the main MVA steering class.
This is the base class for the ROOT Random number generators.
A TTree represents a columnar dataset.
virtual Int_t Fill()
Fill all branches.
virtual void ResetBranchAddresses()
Tell all of our branches to drop their current objects and allocate new ones.
virtual Int_t Branch(TCollection *list, Int_t bufsize=32000, Int_t splitlevel=99, const char *name="")
Create one branch for each element in the collection.