Nearest Neighbor-Clustering Algorithm Based on Hierarchical Optimization Strategy

In order to overcome the shortcoming of nearest neighbor-clustering algorithm in the cluster center determined, the cluster width of the acquisition, and the hidden nodes learning. A FCM strategy is being proposed to determine the cluster center, introducing the target function and the LMS method to make the cluster width adjusted adaptively, and a pruning strategy is adopted to cut the redundant hidden nodes. The simulation results in the nearest neighbor-clustering based on hierarchical optimization strategy show that the algorithms are greatly improved in the learning accuracy and speed.