SVM-Based Local Search for Gene Selection and Classification of Microarray Data

This paper presents a SVM-based local search (SVM-LS) approach to the problem of gene selection and classification of microarray data. The proposed approach is highlighted by the use of a SVM classifier both as an essential part of the evaluation function and as a “provider” of useful information for designing effective LS algorithms. The SVM-LS approach is assessed on a set of three well-known data sets and compared with some best algorithms from the literature.

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