VC-DomLEM: Rule induction algorithm for variable consistency rough set approaches
نویسندگان
چکیده
We present a general rule induction algorithm based on sequential covering, suitable for variable consistency rough set approaches. This algorithm, called VC-DomLEM, can be used for both ordered and non-ordered data. In the case of ordered data, the rough set model employs dominance relation, and in the case of non-ordered data, it employs indiscernibility relation. VC-DomLEM generates a minimal set of decision rules. To this end, the following rule consistency measures are applied: -consistency, ′-consistency, and -consistency. We analyze properties of induced decision rules, and discuss conditions of correct rule induction. Moreover, we show how to improve rule induction efficiency due to application of monotonic consistency measures.
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