Robust clustering based on trimming

Producción Científica

Bibliographic Details
Authors: García Escudero, Luis Ángel, Mayo Iscar, Agustín
Format: article
Status:Published version
Publication Date:2024
Country:España
Institution:Universidad de Valladolid
Repository:UVaDOC. Repositorio Documental de la Universidad de Valladolid
OAI Identifier:oai:uvadoc.uva.es:10324/72570
Online Access:https://doi.org/10.1002/wics.1658
https://uvadoc.uva.es/handle/10324/72570
Access Level:Open access
Keyword:clustering
model-based clustering
robustness
trimming
1209 Estadística
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spelling Robust clustering based on trimmingGarcía Escudero, Luis ÁngelMayo Iscar, Agustínclusteringmodel-based clusteringrobustnesstrimming1209 EstadísticaProducción CientíficaClustering is one of the most widely used unsupervised learning techniques. However, it is well-known that outliers can have a significantly adverse impact on commonly applied clustering methods. On the other hand, clustered outliers can be particularly detrimental to (even robust) statistical procedures. Therefore, it makes sense to combine concepts from Robust Statistics and Cluster Analysis to deal with both clusters and outliers simultaneously through robust clustering approaches. Among the existing robust clustering techniques, we focus on those that rely on (impartial) trimming. Trimming offers the user an easy interpretation, as standard well-known clustering methods are applied after a fraction of the potentially most outlying observations is removed. This trimming approach, when combined with appropriate constraints on the clusters' dispersion parameters, has shown a good performance and can be implemented efficiently thorough available algorithms.Este trabajo forma parte del proyecto de investigación PID2021-128314NB-I00 financiado por MCIN/AEI/10.13039/501100011033/FEDER.Wiley2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.1002/wics.1658https://uvadoc.uva.es/handle/10324/72570reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolidinstname:Universidad de ValladolidIngléshttps://wires.onlinelibrary.wiley.com/doi/10.1002/wics.1658info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/oai:uvadoc.uva.es:10324/725702026-06-13T12:44:47Z
dc.title.none.fl_str_mv Robust clustering based on trimming
title Robust clustering based on trimming
spellingShingle Robust clustering based on trimming
García Escudero, Luis Ángel
clustering
model-based clustering
robustness
trimming
1209 Estadística
title_short Robust clustering based on trimming
title_full Robust clustering based on trimming
title_fullStr Robust clustering based on trimming
title_full_unstemmed Robust clustering based on trimming
title_sort Robust clustering based on trimming
dc.creator.none.fl_str_mv García Escudero, Luis Ángel
Mayo Iscar, Agustín
author García Escudero, Luis Ángel
author_facet García Escudero, Luis Ángel
Mayo Iscar, Agustín
author_role author
author2 Mayo Iscar, Agustín
author2_role author
dc.subject.none.fl_str_mv clustering
model-based clustering
robustness
trimming
1209 Estadística
topic clustering
model-based clustering
robustness
trimming
1209 Estadística
description Producción Científica
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
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dc.identifier.none.fl_str_mv https://doi.org/10.1002/wics.1658
https://uvadoc.uva.es/handle/10324/72570
url https://doi.org/10.1002/wics.1658
https://uvadoc.uva.es/handle/10324/72570
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://wires.onlinelibrary.wiley.com/doi/10.1002/wics.1658
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https://creativecommons.org/licenses/by/4.0/
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dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
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instname:Universidad de Valladolid
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