Utility metric for unsupervised feature selection

Feature selection techniques are very useful approaches for dimensionality reduction in data analysis. They provide interpretable results by reducing the dimensions of the data to a subset of the original set of features. When the data lack annotations, unsupervised feature selectors are required fo...

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Detalles Bibliográficos
Autores principales: Villa, Amalia, Mundanad Narayanan, Abhijith, Van Huffel, Sabine, Bertrand, Alexander, Varon, Carolina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Algorithms and Analysis of Algorithms
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080425/
https://www.ncbi.nlm.nih.gov/pubmed/33981839
http://dx.doi.org/10.7717/peerj-cs.477

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080425/
https://www.ncbi.nlm.nih.gov/pubmed/33981839
http://dx.doi.org/10.7717/peerj-cs.477

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