A Kolmogorov-Smirnov Correlation-Based Filter for Microarray Data

Authors:
Jacek Biesiada;Włodzisław Duch
Affiliations:
Division of Computer Methods, Department of Electrotechnology, The Silesian University of Technology, Katowice, Poland 40-019 and Division of Biomedical Informatics, Cincinnati Children Hosptial M ...;Department of Informatics, Nicolaus Copernicus University, Toruń, Poland
Venue:
Neural Information Processing
Year:
2008

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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 Correlation-Based 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.