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Multivariate statistical methods and data mining in particle physics (4/4)
<!--HTML-->The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the...
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Lenguaje: | eng |
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2008
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Acceso en línea: | http://cds.cern.ch/record/1111146 |
_version_ | 1780914294378987520 |
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author | Glen COWAN |
author_facet | Glen COWAN |
author_sort | Glen COWAN |
collection | CERN |
description | <!--HTML-->The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented. |
id | cern-1111146 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2008 |
record_format | invenio |
spelling | cern-11111462022-11-03T08:16:11Zhttp://cds.cern.ch/record/1111146engGlen COWANMultivariate statistical methods and data mining in particle physics (4/4)Multivariate statistical methods and data mining in particle physics (4/4)Academic Training Lecture Regular Programme<!--HTML-->The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.oai:cds.cern.ch:11111462008 |
spellingShingle | Academic Training Lecture Regular Programme Glen COWAN Multivariate statistical methods and data mining in particle physics (4/4) |
title | Multivariate statistical methods and data mining in particle physics (4/4) |
title_full | Multivariate statistical methods and data mining in particle physics (4/4) |
title_fullStr | Multivariate statistical methods and data mining in particle physics (4/4) |
title_full_unstemmed | Multivariate statistical methods and data mining in particle physics (4/4) |
title_short | Multivariate statistical methods and data mining in particle physics (4/4) |
title_sort | multivariate statistical methods and data mining in particle physics (4/4) |
topic | Academic Training Lecture Regular Programme |
url | http://cds.cern.ch/record/1111146 |
work_keys_str_mv | AT glencowan multivariatestatisticalmethodsanddatamininginparticlephysics44 |