A Pre-processing Model for Feature Extraction Based on K-mean, PSO and ABC

Abstract

To achieve efficient rule mining feature selection or preprocessing is need to be handled before the implementing the optimization technique. For these different methods are available. In the proposed model $K$ means clustering is used to generate the clusters. Then PSO-ABC hybrid approach is for feature optimization. For the obtained result, PSO-ABC represent more normalized features as compared to using PSO only.