void mlpbuild(){
	//mlp setting
	TString ccdirectory= "rootfile/cc/";
	TString ncdirectory= "rootfile/nc/";
	TString backgdirectory= "rootfile/backg/";
	TString exodirectory= "rootfile/exo/";
	Int_t nbg = 3;
	TString bgrootfiles[nbg];
	bgrootfiles[0]=ccdirectory + "ccq100-ariadne-1.root";
	bgrootfiles[1]=ncdirectory + "ncq100-ariadne-1.root";
	bgrootfiles[2]=backgdirectory + "php-dir-et30-herwig-10.root";

	Int_t nvar = 4;
	Float_t CAL_E,CAL_Pt,CAL_px,CAL_py,CAL_pz;
	
	TString layer = "CAL_E,CAL_Pt,CAL_px,CAL_py,CAL_pz:5:type";

	Int_t ntrain=100;



/***********************************************************************************/
	Int_t i, j;
	//prepare signal TTree
	TFile f(exodirectory+"susy.root");
	TTree *signal = (TTree *) f.Get("h1");
	

	//prepare background TChain and background TTree
	TChain background("h1");
	for (i=1; i<nbg; i++){
	    background.Add(bgrootfiles[i]);
	}

	background.SetBranchStatus("CAL_E", 1);
	background.SetBranchStatus("CAL_Pt", 1);
	background.SetBranchStatus("CAL_px", 1);
	background.SetBranchStatus("CAL_py", 1);
	background.SetBranchStatus("CAL_pz", 1);
	signal->SetBranchStatus("CAL_E", 1);
	signal->SetBranchStatus("CAL_Pt", 1);
	signal->SetBranchStatus("CAL_px", 1);
	signal->SetBranchStatus("CAL_py", 1);
	signal->SetBranchStatus("CAL_pz", 1);
	
	//prepare branches address
	Int_t type; //declared type: sig for 1 and bg for 0
	TTree *input = new TTree("output", "output TTree");
	signal->SetBranchAddress("CAL_E", &CAL_E);
	signal->SetBranchAddress("CAL_Pt", &CAL_Pt);
	signal->SetBranchAddress("CAL_px", &CAL_px);
	signal->SetBranchAddress("CAL_py", &CAL_py);
	signal->SetBranchAddress("CAL_pz", &CAL_pz);
	background.SetBranchAddress("CAL_E", &CAL_E);
	background.SetBranchAddress("CAL_Pt", &CAL_Pt);
	background.SetBranchAddress("CAL_px", &CAL_px);
	background.SetBranchAddress("CAL_py", &CAL_py);
	background.SetBranchAddress("CAL_pz", &CAL_pz);
	input->Branch("CAL_E", &CAL_E,"CAL_E/F");
	input->Branch("CAL_Pt", &CAL_Pt,"CAL_Pt/F");
	input->Branch("CAL_px", &CAL_px,"CAL_pz/F");
	input->Branch("CAL_py", &CAL_py,"CAL_py/F");
	input->Branch("CAL_pz", &CAL_pz,"CAL_pz/F");
	input->Branch("type", &type,"type/I");

	type = 1;
	for (i = 0; i < signal->GetEntries(); i++) {
	signal->GetEntry(i,0);
	input->Fill();
	}
	
	type = 0;
	for (i = 0; i < background.GetEntries(); i++) {
	background.GetEntry(i,0);
	input->Fill();
	}

	//Build NN with input layer statement, weight
	TMultiLayerPerceptron *mlp = new TMultiLayerPerceptron(layer, "CAL_Pt", input,"Entry$%2", "(Entry$+1)%2");

	Train NN ntrain times	
	mlp->Train(ntrain, "text,graph,update=10");
}