Look for the best variable using MC
An analysis was done in order to seen which variables are the best when all variable in the HAWC data stream were used.
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Slide 1 of 8
Choose the best variable
The first plot show the variables that have at least one ranking point with a value less or equal to 2. The second is the same but it has a value less or equal to 4.
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Slide 2 of 8
New Network Training using Real Data
Three networks were trained using Real Data:
Using 15 inputs:
Using 4 inputs:
Compactness
rec.PINC
rec.LDFAmp
rec.LDFChi2
Using 6 inputs:
Compactness
rec.PINC
rec.LDFAmp
rec.LDFChi2
rec.SFCFChi2
rec.gammaleLLH
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Slide 3 of 8
Conditions
Real data were used to training and verification.
/data/scratch/userspace/pretz/scrappy-platypus-optimization/
Both stages were applied the following cuts:
rec.coreFideScale < 100 [Events are inside of the HAWC ].
rec.CxPE40 > 0.
Crab maps were made using the month: January and February 2017
/data/archive/hawcroot/data/hawc/reconstructed/hawcprod/v2.02.02/config-38125/reco_xcdf/
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Slide 4 of 8
Real data vs MC
In the training stage, I should apply a cut in Energy
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Slide 5 of 8
Look the maps in Bin 0
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Slide 6 of 8
Ranking using real data
I don't know why rec.nTankAvail have a good ranking. Maybe it has different value in both files (MC as signal and Real data as Bkg)
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Slide 7 of 8
Weekly goals
Work on the version 2 of disMax
Read information about BDT
Train a BDT with 15 inputs
Research why don't have a better result when I use real data (Maybe I have a better result if I apply one cut in Energy)
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Slide 8 of 8