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Talk21 min

Feature ranking based on subtraction methods

Paul Glaysher · CERN

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About

The input variables of ML methods in physics analysis are often highly correlated and figuring out which ones are the most important ones for the classification turns out to be a non-trivial tasks. We compare the standard method of TMVA to rank variables with a several newly developed methods based on iterative removal for the use case of a search for top pair associated Higgs production (ttH) in the Higgs to b-pair decay channel..

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The talk

  1. Feature ranking based on subtraction methods 2019-04-17 · 21 min · CERN's player

Credits and licence

Institution
CERN
Department
LPCC Workshops
Speaker
Paul Glaysher
Year
2019
Language
English
Subjects
Computer science
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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