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 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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Categories
Instrumentation and Detectors
High Energy Physics - Experiment
Data Analysis, Statistics and Probability
