On linear dimension reduction based on diagonalization of scatter matrices for bioinformatics downstream analyses

Dimension reduction is often a preliminary step in the analysis of data sets with a large number of variables. Most classical, both supervised and unsupervised, dimension reduction methods such as principal component analysis (PCA), independent component analysis (ICA) or sliced inverse regression (...

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Detalles Bibliográficos
Autores principales: Fischer, Daniel, Nordhausen, Klaus, Oja, Hannu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7770551/
https://www.ncbi.nlm.nih.gov/pubmed/33385080
http://dx.doi.org/10.1016/j.heliyon.2020.e05732

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7770551/
https://www.ncbi.nlm.nih.gov/pubmed/33385080
http://dx.doi.org/10.1016/j.heliyon.2020.e05732

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