Classifying LEP Data with Support Vector Algorithms

1999/05/17 by P. Vannerem, K. -R. Mueller, Vannerem, P. +7
Computer Science · Physics and Astronomy · #Algorithms and Data Compression #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Metaheuristic Optimization Algorithms Research #Neural Networks and Applications #hep-ex

paper · pdf · doi:10.48550/arxiv.hep-ex/9905027

7 pages, 4 figures, submitted to proceedings of AIHENP99, Crete, April 1999

arxiv created 1999/05/17 · openalex publication_date 1999/05/17 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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