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Data mining is used to extract potential information from data base. Rule induction is used to extract information from data base and display it in IF-THEN rule format. First the classification algorithm builds a predictive model from the training data set and then measure the accuracy of the model by using test data set. This paper proposes a hybrid rule induction algorithm using Cooperative Particle Swarm (PSO) with Tabu Search (TS), and Ant Colony Optimization (ACO). Real world data base consist of both nominal and continuous attributes. ACO based classification algorithms perform well in nominal data base.
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