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

2012/10/25 by Vladimir Vava Gligorov, Mike Williams · 2 citations
Physics and Astronomy · #hep-ex #physics.data-an #physics.ins-det

paper · pdf · doi:10.1088/1748-0221/8/02/p02013

10 pages, 2 figures

arxiv created 2012/10/25 · arxiv updated 2015/06/11

Abstract

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.

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