A Kolmogorov-Smirnov Correlation-Based Filter for Microarray Data

Abstract. A filter algorithm using F-measure has been used with feature redundancy removal based on the Kolmogorov-Smirnov (KS) test for rough equality of statistical distributions. As a result computationally efficient K-S CorrelationBased Selection algorithm has been developed and tested on three high-dimensional microarray datasets using four types of classifiers. Results are quite encouraging and several improvements are suggested.

• Type: Conference
• Year: 2007
• Where: ICONIP
• Authors: Jacek Biesiada, Wlodzislaw Duch
• Keywords: Feature Redundancy Removal, ICONIP 2007, Information Technology, Rough Equality, filter Algorithm