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In this article, the hybridization between the Ant Colony Optimization and Adaboost with Decision Trees (C4.5) to improve the classification is proposed. The experiments show the usefulness of the approach.<\/jats:p>","DOI":"10.4018\/ijirr.2018100103","type":"journal-article","created":{"date-parts":[[2018,7,18]],"date-time":"2018-07-18T15:28:45Z","timestamp":1531927725000},"page":"39-50","source":"Crossref","is-referenced-by-count":3,"title":["Feature Subset Selection Using Ant Colony Optimization for a Decision Trees Classification of Medical Data"],"prefix":"10.4018","volume":"8","author":[{"given":"Abdiya","family":"Alaoui","sequence":"first","affiliation":[{"name":"EEDIS Laboratory, Department of Computer Science, Djillali Liabes University, Sidi Bel Abb\u00e8s, Algeria"}]},{"given":"Zakaria","family":"Elberrichi","sequence":"additional","affiliation":[{"name":"EEDIS Laboratory, Department of Computer Science, Djillali Liabes University, Sidi Bel Abb\u00e8s, Algeria"}]}],"member":"2432","reference":[{"key":"IJIRR.2018100103-0","unstructured":"Al-Ani, A. (2005). Ant Colony Optimization for feature subset selection. 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