Tailored classification by supervised divergence decision tree algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00335098" target="_blank" >RIV/68407700:21340/19:00335098 - isvavai.cz</a>
Result on the web
<a href="https://indico.fjfi.cvut.cz/event/114/" target="_blank" >https://indico.fjfi.cvut.cz/event/114/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Tailored classification by supervised divergence decision tree algorithm
Original language description
Binary classification is a common task frequently used in high energy physics in order to separate the relevant signal from background in particle decay channels. Firstly, this paper examines behaviour of the kernel density estimators for model distributions and describes discrepancy method (D-method) for selecting the bandwidth based on evaluation of divergences or distances between two estimated distributions. Secondly, binary classification of provided HEP data set is performed by the supervised divergence decision tree algorithm incorporating R'enyi divergence measure in its nodes. It was found that the precise knowledge of any classification algorithm enables to tailor data for this specific classifier and thus to attain better results
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of SPMS 2019 - Stochastic and Physical Monitoring Systems
ISBN
978-80-01-06659-1
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
39-47
Publisher name
Česká technika - nakladatelství ČVUT
Place of publication
Praha
Event location
Dobřichovice
Event date
Jun 20, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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