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...

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Detalles Bibliográficos
Autores principales: Aziz, Rabia, Verma, C.K., Srivastava, Namita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Regular Article
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

Internet

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

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