Example of a Multi Layer Perceptron For a LEP search for invisible Higgs boson, a neural network was used to separate the signal from the background passing some selection cuts.
Here is a simplified version of this network, taking into account only WW events.
Processing /mnt/build/workspace/root-makedoc-v614/rootspi/rdoc/src/v6-14-00-patches/tutorials/mlp/mlpHiggs.C...
Training the Neural Network
Epoch: 0 learn=0.127703 test=0.126764
Epoch: 10 learn=0.0966153 test=0.0940247
Epoch: 20 learn=0.0939027 test=0.0909187
Epoch: 30 learn=0.0927131 test=0.088778
Epoch: 40 learn=0.0918599 test=0.0885711
Epoch: 50 learn=0.0914885 test=0.0880977
Epoch: 60 learn=0.090818 test=0.0885531
Epoch: 70 learn=0.090233 test=0.0875801
Epoch: 80 learn=0.0896966 test=0.0864744
Epoch: 90 learn=0.0894374 test=0.0867297
Epoch: 99 learn=0.0889444 test=0.0862591
Training done.
test.py created.
Network with structure: @msumf,@ptsumf,@acolin:5:3:type
inputs with low values in the differences plot may not be needed
@msumf -> 0.0183069 +/- 0.0117043
@ptsumf -> 0.0268229 +/- 0.0397225
@acolin -> 0.028166 +/- 0.0357126
void mlpHiggs(
Int_t ntrain=100) {
const char *fname = "mlpHiggs.root";
} else {
printf("accessing %s file from http://root.cern.ch/files\n",fname);
}
if (!input) return;
TTree *simu =
new TTree(
"MonteCarlo",
"Filtered Monte Carlo Events");
Float_t ptsumf, qelep, nch, msumf, minvis, acopl, acolin;
simu->
Branch(
"ptsumf", &ptsumf,
"ptsumf/F");
simu->
Branch(
"qelep", &qelep,
"qelep/F");
simu->
Branch(
"nch", &nch,
"nch/F");
simu->
Branch(
"msumf", &msumf,
"msumf/F");
simu->
Branch(
"minvis", &minvis,
"minvis/F");
simu->
Branch(
"acopl", &acopl,
"acopl/F");
simu->
Branch(
"acolin", &acolin,
"acolin/F");
simu->
Branch(
"type", &type,
"type/I");
type = 1;
for (i = 0; i < sig_filtered->
GetEntries(); i++) {
}
type = 0;
}
"ptsumf",simu,"Entry$%2","(Entry$+1)%2");
mlp->
Train(ntrain,
"text,graph,update=10");
ana.GatherInformations();
ana.CheckNetwork();
ana.DrawDInputs();
ana.DrawNetwork(0,"type==1","type==0");
TH1F *bg =
new TH1F(
"bgh",
"NN output", 50, -.5, 1.5);
TH1F *sig =
new TH1F(
"sigh",
"NN output", 50, -.5, 1.5);
params[0] = msumf;
params[1] = ptsumf;
params[2] = acolin;
}
for (i = 0; i < sig_filtered->
GetEntries(); i++) {
params[0] = msumf;
params[1] = ptsumf;
params[2] = acolin;
}
legend->
AddEntry(bg,
"Background (WW)");
legend->
AddEntry(sig,
"Signal (Higgs)");
delete input;
}
- Author
- Christophe Delaere
Definition in file mlpHiggs.C.