Understand
The paper describes an application of the tree classification method Random Forest (RF), as used in the analysis of data from the ground-based gamma telescope MAGIC.
- In such telescopes, cosmic gamma-rays are observed and have to be discriminated against a dominating background of hadronic cosmic-ray particles.
- We describe the application of RF for this gamma/hadron separation.
- The RF method often shows superior performance in comparison with traditional semi-empirical techniques.
Built on
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L.Breiman, FORTRAN program Random Forests, Version 3.1, and L.Breiman, Manual On Setting Up, Using, And Understanding Random Forests V3. 1, both available at http://oz.berkeley.edu/users/breiman
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R. Brun, F. Rademakers, http://root.cern.ch/
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Then
T. Hengstebeck, PhD thesis, Mathematisch-Naturwissenschaftliche Fakultät I, Humboldt-Universität zu Berlin, März 2007. Available at URL http://edoc.hu-berlin.de/docviews/abstract.php?id=28015
2007
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