RT Journal Article
T1 Implementation of the Random Forest method for the Imaging Atmospheric Cherenkov Telescope MAGIC
A1 Antoranz Canales, Pedro
A1 Barrio Uña, Juan Abel
A1 Contreras González, José Luis
A1 Fonseca González, María Victoria
A1 López Moya, Marcos
A1 Miranda Pantoja, José Miguel
A1 Nieto Castaño, Daniel
AB The paper describes an application of the tree classification method Random Forest (RF), as used in the analysis of data from the ground-based gamma telescope MAGIC. In such telescopes, cosmic gamma-rays are observed and have to be discriminated against a dominating background of hadronic cosmic-ray particles. We describe the application of RF for this gamma/hadron separation. The RF method often shows superior performance in comparison with traditional semi-empirical techniques. Critical issues of the method and its implementation are discussed. An application of the RF method for estimation of a continuous parameter from related variables, rather than discrete classes, is also discussed. (C) 2008 Published by Elsevier B.V.
PB Elsevier Science BV
SN 0168-9002
YR 2008
FD 2008-04-11
LK https://hdl.handle.net/20.500.14352/50837
UL https://hdl.handle.net/20.500.14352/50837
LA eng
NO © Elsevier Science.We thank Jens Zimmermann for fruitful discussions about the RF method and for comparisons of the RFmethod with a Neural Net approach.
DS Docta Complutense
RD 7 abr 2025