A Comparative Study to Select a Soft Computing Model for Knowledge Discovery in Data Mining

The ABC algorithm imitates the behaviors of real bees in finding food sources and sharing the information with other bees. The said algorithm works based on three categories of bees, that is, employed, onlooker and scout bees that communicate with each other in sharing the information of the food sources Since ABC algorithm is simple in concept, easy to implement, and has fewer control parameters, it has been widely used in many fields. This paper concerns primarily about how to use artificial bee colony to extract the knowledge from the data mining on the Boston city data .In this paper, we have formed the association rule of data by PCA and then used other soft computing model like Artificial Neural Network, PSO and ABC algorithm along with fuzzy logic. After that, selected the optimal model based on the minimum error and that will be used to discovered the knowledge in data.