Multiobjective genetic rule selection as a data mining postprocessing procedure

In this paper, we show the usefulness of multiobjective genetic rule selection as a postprocessing procedure in data mining for pattern classification problems. First we extract a prespecified number of rules using a data mining technique. Then we apply multiobjective genetic rule selection to the extracted rules. Experimental results show that multiobjective genetic rule selection significantly decreases the number of extracted rules while improving their classification accuracy.