A Population Based Feature Subset Selection Algorithm Guided by Fuzzy Feature Dependency
Population-based (or evolutionary) algorithms have been attracting an increased attention due to their powerful search capabilities. For the particular problem of feature selection, population-based methods aim to produce better ”or fitter” future generations that contain more informative subsets of features. It is well-known that feature subset selection is a very challenging optimization problem, especially when dealing with datasets that contain large number of features. Most of the commonly used population-based feature selection methods use operators that do not take into account relationships between features to generate future subsets, which can have an impact on their capabilities to properly explore the search space. We present here a new population-based feature selection method that utilize dependency between features to guide the search. In addition, a novel method for estimating dependency between feature pairs is proposed based on the concept of fuzzy entropy. Results obtained from datasets with various sizes indicate the superiority of the proposed method in comparison to some of the well-known methods in the literature.
KeywordsParticle Swarm Optimization Feature Selection Classification Accuracy Feature Selection Method Feature Selection Algorithm
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- 3.Frohlich, H., Chapelle, O., Scholkopf, B.: Feature Selection for Support Vector Machines by Means of Genetic Algorithms. In: Proc. IEEE Intl. Conf. Tools with Artificial Intelligence (ICTAI 2003), pp. 142–148 (2003)Google Scholar
- 4.Al-Ani, A.: Feature Subset Selection Using Ant Colony Optimization. Int. Journal of Computational Intelligence 2, 53–58 (2005)Google Scholar
- 5.Firpi, H.A., Goodman, E.: Swarmed Feature Selection. In: Proc. Applied Imagery Pattern Recognition Workshop, pp. 112–118 (2004)Google Scholar
- 9.Khushaba, R.N., Kodagoda, S., Lal, S., Dissanayake, G.: Driver Drowsiness Classification Using Fuzzy Wavelet-Packet-Based Feature-Extraction Algorithm 58(1), 121–131 (2011)Google Scholar
- 10.AlSukker, A., Khushaba, R., Al-Ani, A.: Enhancing the Diversity of Genetic Algorithm for Improved Feature Selection. In: IEEE International Conference on Systems, Man, and Cybernetics, SMC 2010 (2010)Google Scholar