Using ACO and rough set theory to feature selection

In this paper we propose a model to feature selection based on ant colony and rough set theory (RST). The objective is to find the reducts. RST offers the heuristic function to measure the quality of one feature subset. We have studied three variants of ant's algorithms and the influence of the parameters on the performance both in terms of quality of the results and the number of reducts found. Experimental results show this hybrid approach shows interesting advantages when compared with other heuristic methods.

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