Tagging heavy flavours with boosted decision trees

Details Tagging heavy flavours with boosted decision trees Tagging heavy flavours with boosted decision trees

2007-02-05

arxiv.org/abs/physics/0702041v2

Physics

Data Analysis, Statistics and Probability

12 pages, 13 figures

Scientific paper

This paper evaluates the performance of boosted decision trees for tagging b-jets. It is shown, using a Monte Carlo simulation of $WH \to l\nu q\bar{q}$ events that boosted decision trees outperform feed-forward neural networks. The results show that for a b-tagging efficiency of 60% the light jet rejection given by boosted decision trees is about 35% higher than that given by neural networks.

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