Intelligent water drops algorithm for rough set feature selection

Authors:
Basem O. Alijla;Lim Chee Peng;Ahamad Tajudin Khader;Mohammed Azmi Al-Betar
Affiliations:
School of Computer Sciences, Universiti Sains Malaysia, Pinang, Malaysia;Centre for Intelligent Systems Research, Deakin University, Australia;School of Computer Sciences, Universiti Sains Malaysia, Pinang, Malaysia;School of Computer Sciences, Universiti Sains Malaysia, Pinang, Malaysia, Department of Computer Science, Jadara University, Irbid, Jordan
Venue:
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Year:
2013

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Abstract

In this article; Intelligent Water Drops (IWD) algorithm is adapted for feature selection with Rough Set (RS). Specifically, IWD is used to search for a subset of features based on RS dependency as an evaluation function. The resulting system, called IWDRSFS (Intelligent Water Drops for Rough Set Feature Selection), is evaluated with six benchmark data sets. The performance of IWDRSFS are analysed and compared with those from other methods in the literature. The outcomes indicate that IWDRSFS is able to provide competitive and comparable results. In summary, this study shows that IWD is a useful method for undertaking feature selection problems with RS.