Volatility of selected separators/classifiers wrt. data sets from field of particle physics

0368174 - ÚI 2012 CZ eng V - Research Report
Jiřina, Marcel - Hakl, František
Volatility of selected separators/classifiers wrt. data sets from field of particle physics.
Prague: ICS AS CR, 2011. 10 s. Technical Report, V-1126.
R&D Projects: GA MŠMT(CZ) 1M0567
Institutional research plan: CEZ:AV0Z10300504
Keywords : multivariate data * volatility * classification * signal-background separation * physics event data * particle physics
Subject RIV: BB - Applied Statistics, Operational Research

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.
Permanent Link: http://hdl.handle.net/11104/0202590