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This paper surveys main principles of feature selection and their recent applications in big data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and embedded approaches to feature selection, we formulate feature selection as a combinatorial optimization or search problem and categorize feature selection methods into exhaustive search, heuristic search, and hybrid...
We propose an algorithm of searching for good discriminative gene sets (DGSs) in microarray cancer data, which we call active mining discriminative gene sets (AM-DGS). Tests in the leukemia data set and the prostate data set indicate that our method is able to achieve better accuracy with much smaller DGSs compared to 3 widely used methods, i.e., TS, FS, and SVM-RFE.
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