Original title: Volatility of selected separators/classifiers wrt. data sets from field of particle physics
Authors: Jiřina, Marcel ; Hakl, František
Document type: Research reports
Year: 2011
Language: eng
Series: Technical Report, volume: V-1126
Abstract: We study the volatility, i.e. influence of random changes in data sets to overall separation/classification behavior of separators/classifiers. This is motivated by the fact, that simulated data and true data from ATLAS experiment may differ, and a question arises what if separators or cuts are optimized for simulated data, and then used for true data from the experiment. This behavior was studied using simulated data modified by artificial distortions of known size. We found that even slight change in data sets causes a little worse result than supposed but, surprisingly, even relatively large distortions give then nearly the same results. Only truly great variations cause degradation of separation quality of separator/classifier as well as of the cuts method.
Keywords: classification; multivariate data; particle physics; physics event data; signal-background separation; volatility
Project no.: CEZ:AV0Z10300504 (CEP), 1M0567 (CEP)
Funding provider: GA MŠk
Rights: This work is protected under the Copyright Act No. 121/2000 Coll.

Institution: Institute of Computer Science AS ČR (web)
Original record: http://hdl.handle.net/11104/0202590

Permalink: http://www.nusl.cz/ntk/nusl-77422


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