Abstract
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. Critical issues of the method and its implementation are discussed. An application of the RF method for estimation of a continuous parameter from related variables, rather than discrete classes, is also discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 424-432 |
| Number of pages | 9 |
| Journal | Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment |
| Volume | 588 |
| Issue number | 3 |
| DOIs | |
| State | Published - Apr 11 2008 |
Keywords
- Classification
- Decision tree
- Discrimination
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