A Bee Colony Optimization Based Improved to Hierarhical Clustering

Clustering is having the significance to generate effective data segments based on feature and dimension evaluation. In this work, an ABC improved Hierarchical clustering method is defined. The method has divided the clustering activities for different types of bees with their relative role assignment. The scout bee defined as the controller and the onlooker bees are defined as the cluster agents. Based on these agents, the cluster segments are evaluated under feature specific parametric evaluation. The work is applied on two benchmark datasets. The proposed work model has improved the accuracy and reliability clustering process.