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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 (...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2020
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| 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 |