Classifying LEP Data with Support Vector Algorithms
High Energy Physics - Experiment
2007-05-23 v1
Abstract
We have studied the application of different classification algorithms in the analysis of simulated high energy physics data. Whereas Neural Network algorithms have become a standard tool for data analysis, the performance of other classifiers such as Support Vector Machines has not yet been tested in this environment. We chose two different problems to compare the performance of a Support Vector Machine and a Neural Net trained with back-propagation: tagging events of the type e+e- -> ccbar and the identification of muons produced in multihadronic e+e- annihilation events.
Keywords
Cite
@article{arxiv.hep-ex/9905027,
title = {Classifying LEP Data with Support Vector Algorithms},
author = {P. Vannerem and K. -R. Mueller and B. Schoelkopf and A. Smola and S. Soldner-Rembold},
journal= {arXiv preprint arXiv:hep-ex/9905027},
year = {2007}
}
Comments
7 pages, 4 figures, submitted to proceedings of AIHENP99, Crete, April 1999