Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree

High-level triggering is a vital component in many modern particle physics experiments. This paper describes a modification to the standard boosted decision tree (BDT) classifier, the so-called "bonsai" BDT, that has the following important properties: it is more efficient than traditional...

Descripción completa

Detalles Bibliográficos
Autores principales: Gligorov, V.V., Williams, Mike
Lenguaje:eng
Publicado: 2012
Materias:
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1088/1748-0221/8/02/P02013
http://cds.cern.ch/record/1490195
_version_ 1780926371355164672
author Gligorov, V.V.
Williams, Mike
author_facet Gligorov, V.V.
Williams, Mike
author_sort Gligorov, V.V.
collection CERN
description High-level triggering is a vital component in many modern particle physics experiments. This paper describes a modification to the standard boosted decision tree (BDT) classifier, the so-called "bonsai" BDT, that has the following important properties: it is more efficient than traditional cut-based approaches; it is robust against detector instabilities, and it is very fast. Thus, it is fit-for-purpose for the online running conditions faced by any large-scale data acquisition system.
id cern-1490195
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2012
record_format invenio
spelling cern-14901952022-08-10T20:35:33Zdoi:10.1088/1748-0221/8/02/P02013http://cds.cern.ch/record/1490195engGligorov, V.V.Williams, MikeEfficient, reliable and fast high-level triggering using a bonsai boosted decision treeDetectors and Experimental TechniquesHigh-level triggering is a vital component in many modern particle physics experiments. This paper describes a modification to the standard boosted decision tree (BDT) classifier, the so-called "bonsai" BDT, that has the following important properties: it is more efficient than traditional cut-based approaches; it is robust against detector instabilities, and it is very fast. Thus, it is fit-for-purpose for the online running conditions faced by any large-scale data acquisition system.arXiv:1210.6861oai:cds.cern.ch:14901952012-10-26
spellingShingle Detectors and Experimental Techniques
Gligorov, V.V.
Williams, Mike
Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
title Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
title_full Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
title_fullStr Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
title_full_unstemmed Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
title_short Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
title_sort efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
topic Detectors and Experimental Techniques
url https://dx.doi.org/10.1088/1748-0221/8/02/P02013
http://cds.cern.ch/record/1490195
work_keys_str_mv AT gligorovvv efficientreliableandfasthighleveltriggeringusingabonsaiboosteddecisiontree
AT williamsmike efficientreliableandfasthighleveltriggeringusingabonsaiboosteddecisiontree

Ejemplares similares