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The proposed method is experimentally compared with other hybrid Rough Set methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) and the empirical results reveal that the proposed approach could be used for feature selection as this performs better in terms of finding optimal features and doing so in quick time.<\/jats:p>","DOI":"10.2478\/s13537-013-0102-4","type":"journal-article","created":{"date-parts":[[2013,4,1]],"date-time":"2013-04-01T03:16:43Z","timestamp":1364786203000},"source":"Crossref","is-referenced-by-count":4,"title":["Rough set and teaching learning based optimization technique for optimal features selection"],"prefix":"10.2478","volume":"3","author":[{"given":"Suresh","family":"Satapathy","sequence":"first","affiliation":[]},{"given":"Anima","family":"Naik","sequence":"additional","affiliation":[]},{"given":"K.","family":"Parvathi","sequence":"additional","affiliation":[]}],"member":"374","reference":[{"key":"102_CR1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/3-540-33019-4_1","volume":"16","author":"M. 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