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arXiv 0709.3719astro-ph
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随机森林方法在成像大气切伦科夫望远镜MAGIC中的实现

Implementation of the Random Forest Method for the Imaging Atmospheric Cherenkov Telescope MAGIC

J. Albert

摘要:

本文介绍了树分类方法随机森林(RF)的应用程序,用于从地面伽马望远镜MAGIC的数据分析。在这样的望远镜中,宇宙伽马射线被观测到,并且必须与强子宇宙射线粒子的主导背景区分开来。我们描述了RF的应用,这种伽马/强子分离。与传统的半经验技术相比,RF方法通常表现出优越的性能。该方法及其实施的关键问题进行了讨论。应用RF方法估计的连续参数从相关变量,而不是离散类,也进行了讨论。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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