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UW Classification trees: first comparison with Atwood/Usher trees

UW Classification trees: first comparison with Atwood/Usher trees. Issue: how does the boosted tree scheme compare with Insightful Miner’s multiple tree? Previous comparison was with single trees only. Reminder: This code is all in GlastRelease, accessible to anyone.

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UW Classification trees: first comparison with Atwood/Usher trees

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  1. UW Classification trees: first comparison with Atwood/Usher trees • Issue: how does the boosted tree scheme compare with Insightful Miner’s multiple tree? • Previous comparison was with single trees only. • Reminder: • This code is all in GlastRelease, accessible to anyone T. Burnett

  2. The new Atwood/Usher variables • Fantastic job by Tracy to make these available: • The names are: • CTBbestEneProb CTBprofileProbCTBlastLayerPrCTBtrackerProbCTBparamProbCTBBestEnergyCTBdeltaEoECTBVTXCTBCORECTBGAM • A little niggle: • Can someone tell me the rule on how to capitalize these guys?  • When “energy” is “ene”? • When “prob” is “pr”? T. Burnett

  3. CTBbestEneProb • Tracy recommends 0.1 as a cut on this. For the 10M GR v7r3p1 run, here is the distribution, cut, and corresponding acceptance: ~4 m2 Sr Note: requires onboard filter cut, at least one track T. Burnett

  4. The corresponding E/E distributions for the standard 8 energy bins Note: logarithmic scales! T. Burnett

  5. And, with a 0.4 cut: T. Burnett

  6. The UW version • UW variable: CTgoodCal. • Trained on even events inallGamma-GR-v7r2-merit-TKR-prune.root • 7 different trees, all boosted 10 times: • param: all energies, or separately low, med, high • profile • tracker • lastlayer • Best one seems to be the combination of low, med, high of param • Results are shown for performance on the 10 M runallGamma-v7r3p1-10M-merit.rootallGamma-v7r3p1-10M-merit_1.rootallGamma-v7r3p1-10M-merit_2.root T. Burnett

  7. CTgoodCal results:cut at 0.5 T. Burnett

  8. The corresponding E/E distributions for the standard 8 energy bins Note: logarithmic scales! T. Burnett

  9. Status • Boosted trees seem to be at least equivalent to IM multiple trees • Training can be done by anyone • Next week: compare the following: • CTBVTX with CTvertex • CTBCORE with CTgoodPsf: how do our standard  and  compare? (See Jim’s fits) • Following week • CTBGAM vs. CTgamma T. Burnett

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