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A fuzzy based feature selection from independent component subspace for machine learning classification of microarray data
Feature (gene) selection and classification of microarray data are the two most interesting machine learning challenges. In the present work two existing feature selection/extraction algorithms, namely independent component analysis (ICA) and fuzzy backward feature elimination (FBFE) are used which...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4818349/ https://www.ncbi.nlm.nih.gov/pubmed/27081632 http://dx.doi.org/10.1016/j.gdata.2016.02.012 |