Title of article :
Statistical learning methods in high-energy and astrophysics analysis
Author/Authors :
Zimmermann، نويسنده , , J. and Kiesling، نويسنده , , C.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2004
Abstract :
We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.
Keywords :
Inference , Neutral networks , decision trees , Support Vector Machines , Classification , Regression
Journal title :
Nuclear Instruments and Methods in Physics Research Section A
Journal title :
Nuclear Instruments and Methods in Physics Research Section A
