Feature Extraction

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<!--HTML-->Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

Detalles Bibliográficos
Autor principal: Dr. GLEYZER, Sergei
Lenguaje:eng
Publicado: 2015
Materias:
LPCC Workshops
Acceso en línea:http://cds.cern.ch/record/2067016
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author Dr. GLEYZER, Sergei
author_facet Dr. GLEYZER, Sergei
author_sort Dr. GLEYZER, Sergei
collection CERN
description <!--HTML-->Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.
id cern-2067016
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
record_format invenio
spelling cern-20670162022-11-02T22:33:49Zhttp://cds.cern.ch/record/2067016engDr. GLEYZER, SergeiFeature ExtractionData Science @ LHC 2015 WorkshopLPCC Workshops<!--HTML-->Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.oai:cds.cern.ch:20670162015
spellingShingle LPCC Workshops
Dr. GLEYZER, Sergei
Feature Extraction
title Feature Extraction
title_full Feature Extraction
title_fullStr Feature Extraction
title_full_unstemmed Feature Extraction
title_short Feature Extraction
title_sort feature extraction
topic LPCC Workshops
url http://cds.cern.ch/record/2067016
work_keys_str_mv AT drgleyzersergei featureextraction
AT drgleyzersergei datasciencelhc2015workshop

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