Corpus ID: 237635440

Boosted decision trees in the era of new physics: a smuon analysis case study

@inproceedings{Cornell2021BoostedDT,
  title={Boosted decision trees in the era of new physics: a smuon analysis case study},
  author={Alan S. Cornell and Wesley Doorsamy and Benjamin Fuks and Gerhard Erwin Harmsen and Lara Hannan Mason},
  year={2021}
}
Machine learning algorithms are growing increasingly popular in particle physics analyses, where they are used for their ability to solve difficult classification and regression problems. While the tools are very powerful, they may often be underor mis-utilised. In the following, we investigate the use of gradient boosting techniques as applicable to a generic particle physics problem. We use as an example a Beyond the Standard Model smuon collider analysis which applies to both current and… Expand

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