Feature Selection and Classification of Microarray Data Using Machine Learning Techniques
M. Kumar; S.K. Rath Department of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India
Abstract
Microarray-based gene expression profiling has emerged as an efficient technique for classification, diagnosis, prognosis, and treatment of cancer. The major drawback in microarray data is the “curse of dimensionality problem,” which hinders the useful information of a data set and leads to computational instability. Therefore, selecting relevant genes is a challenging task in microarray data analysis. Most of the existing schemes employ a two-stage process: feature selection (FS) followed by classification. ...
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