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

SYSNO ASEP	0368174
Document Type	V - Research Report
R&D Document Type	The record was not marked in the RIV
Title	Volatility of selected separators/classifiers wrt. data sets from field of particle physics
Author(s)	Jiřina, Marcel (UIVT-O)_{SAI, RID} Hakl, František (UIVT-O)_{SAI, RID, ORCID}
Issue data	Prague: ICS AS CR, 2011
Series	Technical Report
Series number	V-1126
Number of pages	10 s.
Language	eng - English
Country	CZ - Czech Republic
Keywords	multivariate data ; volatility ; classification ; signal-background separation ; physics event data ; particle physics
Subject RIV	BB - Applied Statistics, Operational Research
R&D Projects	1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
Annotation	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.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2012

Number of the records: 1