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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2016-06-01
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| Series: | Genomics Data |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213596016300344 |