Polyoptimizing Genetic Algorithm for Feature Subset Selection
نویسندگان
چکیده
The analysis of large biological data sets that arise in gene expression or proteomics experiments often involves the selection of a subset of the available features that supports efficient classification. Finding multiple, distinct solutions to the feature subset selection problem may lead to increased biological insights. In this paper we address the problem of finding multiple solutions to the feature subset selection problem using a polyoptimizing genetic algorithm which incorporates a dynamic penalty function. We illustrate the approach on an ovarian cancer classification problem using proteomics data.
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تاریخ انتشار 2004