@article{(Open Science Index):https://publications.waset.org/pdf/10009513,
	  title     = {A Fuzzy-Rough Feature Selection Based on Binary Shuffled Frog Leaping Algorithm},
	  author    = {Javad Rahimipour Anaraki and  Saeed Samet and  Mahdi Eftekhari and  Chang Wook Ahn},
	  country	= {},
	  institution	= {},
	  abstract     = {Feature selection and attribute reduction are crucial
problems, and widely used techniques in the field of machine
learning, data mining and pattern recognition to overcome the
well-known phenomenon of the Curse of Dimensionality. This paper
presents a feature selection method that efficiently carries out attribute
reduction, thereby selecting the most informative features of a dataset.
It consists of two components: 1) a measure for feature subset
evaluation, and 2) a search strategy. For the evaluation measure,
we have employed the fuzzy-rough dependency degree (FRFDD)
of the lower approximation-based fuzzy-rough feature selection
(L-FRFS) due to its effectiveness in feature selection. As for the
search strategy, a modified version of a binary shuffled frog leaping
algorithm is proposed (B-SFLA). The proposed feature selection
method is obtained by hybridizing the B-SFLA with the FRDD. Nine
classifiers have been employed to compare the proposed approach
with several existing methods over twenty two datasets, including
nine high dimensional and large ones, from the UCI repository.
The experimental results demonstrate that the B-SFLA approach
significantly outperforms other metaheuristic methods in terms of the
number of selected features and the classification accuracy.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {12},
	  number    = {9},
	  year      = {2018},
	  pages     = {722 - 729},
	  ee        = {https://publications.waset.org/pdf/10009513},
	  url   	= {https://publications.waset.org/vol/141},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 141, 2018},
	}