Volume 422 -
The Tenth Annual Conference on Large Hadron Collider Physics
(LHCP2022) -
Poster Session
Constraining Deep Neural Network classifiers’ systematic uncertainty via input feature space reduction
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Pre-published on:
March 27, 2023
Published on:
June 21, 2023
Abstract
In this work, we show how using a sub-optimal set of input features can lead to higher systematic uncertainty associated with Deep Neural Network classifier predictions. For this study, we considered the case of highly boosted di-jet resonances produced in pp collisions decaying to two b-quarks to be selected against an overwhelming QCD background. Results from a Monte Carlo simulation with HEP pseudo-detectors are shown.
DOI: https://doi.org/10.22323/1.422.0242
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Copyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.