Ensemble Learning in High Energy Physics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00335099" target="_blank" >RIV/68407700:21340/19:00335099 - 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
Ensemble Learning in High Energy Physics
Original language description
One of the core problems of $D^0$ meson decay analysis consists in separating pairs of kaons $K$ and~pions~$pi$ (signal), as the main product of this decay, from combinatoric background. To carry out such separation, complex machine learning methods are required. This study uses Random Forest algorithm with different data pre-processing approaches. The final results are presented both the quality measures of the signal separations and the physically motivated Gaussian distributions of signals separated.
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
11
Pages from-to
27-37
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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