Partition clustering algorithm based on artificial bee colony principal
一种基于蜂群原理的划分聚类算法*

according to the drawback that most of these algorithms have the shortcoming that clustering results are limited by K value which is the number of clusters, this paper proposed a new partition clustering algorithm based on the principal of artificial bee colony. The clustering method introduces the mechanism of artificial bee colony collecting pollen and every clustering center will be considered as a food source.Then the process of gathering data objects will be achieved by the process of finding the food source. In the process of clustering, tightness function is proposed as the fitness to evaluate the cluster center(local) and separation function is introduced to determine the optimal number of clusters (global). Comapared to traditional partition clustering algorithms, this algorithm does not need the value K that is a given number of clusters to realize clustering process. Simulation results show that the algorithm not only can determine the best number of clusters, and can get a higher clustering accuracy. Furthermore, the time complexity of this algorithm is O(n*k3)(k<