Constraining Deep Neural Network classifiers’ systematic uncertainty via input feature space reduction
A. Di Luca*, M. Cristoforetti and R. Iuppa
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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