26 TString outfileName(
"TMVA.root");
30 "!V:!Silent:Color:DrawProgressBar:Transformations=I;D;P;G,D:AnalysisType=Classification");
32 factory->AddVariable(
"myvar1 := var1+var2",
'F');
33 factory->AddVariable(
"myvar2 := var1-var2",
"Expression 2",
"",
'F');
34 factory->AddVariable(
"var3",
"Variable 3",
"units",
'F');
35 factory->AddVariable(
"var4",
"Variable 4",
"units",
'F');
36 factory->AddSpectator(
"spec1 := var1*2",
"Spectator 1",
"units",
'F');
37 factory->AddSpectator(
"spec2 := var1*3",
"Spectator 2",
"units",
'F');
40 TString fname =
"./tmva_class_example.root";
46 input =
TFile::Open(
"http://root.cern.ch/files/tmva_class_example.root",
"CACHEREAD");
49 std::cout <<
"ERROR: could not open data file" << std::endl;
53 std::cout <<
"--- TMVAClassification : Using input file: " << input->
GetName() << std::endl;
65 factory->AddSignalTree(tsignal, signalWeight);
66 factory->AddBackgroundTree(tbackground, backgroundWeight);
70 factory->SetBackgroundWeightExpression(
"weight");
78 factory->PrepareTrainingAndTestTree(mycuts, mycutb,
79 "nTrain_Signal=0:nTrain_Background=0:nTest_Signal=0:nTest_Background=0:SplitMode=Random:NormMode=NumEvents:!V");
83 "!H:NTrials=10:Rules=kFALSE:ControlSubSet=kFALSE:ControlBands=0:ControlWinnow=kFALSE:ControlNoGlobalPruning=kTRUE:ControlCF=0.25:ControlMinCases=2:ControlFuzzyThreshold=kTRUE:ControlSample=0:ControlEarlyStopping=kTRUE:!V");
87 factory->
BookMethod(
TMVA::Types::kRSNNS,
"RMLP",
"!H:VarTransform=N:Size=c(5):Maxit=200:InitFunc=Randomize_Weights:LearnFunc=Std_Backpropagation:LearnFuncParams=c(0.2,0):!V");
89 factory->
BookMethod(
TMVA::Types::kRSVM,
"RSVM",
"!H:Kernel=linear:Type=C-classification:VarTransform=Norm:Probability=kTRUE:Tolerance=0.1:!V");
105 std::cout <<
"==> Wrote root file: " << outputFile->
GetName() << std::endl;
106 std::cout <<
"==> TMVAClassification is done!" << std::endl;
virtual const char * GetName() const
Returns name of object.
virtual Bool_t AccessPathName(const char *path, EAccessMode mode=kFileExists)
Returns FALSE if one can access a file using the specified access mode.
MethodBase * BookMethod(DataLoader *loader, TString theMethodName, TString methodTitle, TString theOption="")
Book a classifier or regression method.
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format...
virtual TObject * Get(const char *namecycle)
Return pointer to object identified by namecycle.
void TrainAllMethods()
Iterates through all booked methods and calls training.
static TFile * Open(const char *name, Option_t *option="", const char *ftitle="", Int_t compress=1, Int_t netopt=0)
Create / open a file.
A specialized string object used for TTree selections.
R__EXTERN TSystem * gSystem
void EvaluateAllMethods(void)
Iterates over all MVAs that have been booked, and calls their evaluation methods. ...
This is the main MVA steering class.
void SetVerbose(Bool_t status)
Method to set verbose mode, that produce extra output.
static TRInterface & Instance()
static method to get an TRInterface instance reference
static Bool_t SetCacheFileDir(const char *cacheDir, Bool_t operateDisconnected=kTRUE, Bool_t forceCacheread=kFALSE)
Sets the directory where to locally stage/cache remote files.
A TTree object has a header with a name and a title.
virtual void Close(Option_t *option="")
Close a file.