关键词: 最近邻, 自适应聚类, 最小生成树, 聚类分析

Abstract: Classical clustering algorithm based on the minimum spanning tree often needs to know the number of clusters beforehand and use static global threshold to cluster, which leads to the performance of the algorithm low and the computation complex for the uneven distributed data. An improved adaptive hierarchical clustering algorithm based on minimum spanning tree is proposed, which automatically generates different thresholds for every cluster to adapt for the uneven distributed data according to the nearest neighbor relationship and adaptively determines the number of clusters. Experiments demonstrate that this algorithm has good performance, especially could cluster effectively for the uneven distributed data.

Key words: nearest neighbor, adaptive clustering, minimum spanning tree, clustering analysis