Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree
Instrumentation and Detectors
2015-06-11 v1 High Energy Physics - Experiment
Data Analysis, Statistics and Probability
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.
Cite
@article{arxiv.1210.6861,
title = {Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree},
author = {Vladimir Vava Gligorov and Mike Williams},
journal= {arXiv preprint arXiv:1210.6861},
year = {2015}
}
Comments
10 pages, 2 figures