关键词: 聚类分析, 弹性网络, 极大熵, 自由能

Abstract: Cluster analysis is a very important clustering tool and is widely used in various scientific projects. And elastic net is a better clustering analysis method, especially in high-dimensional space. And a new Clustering Elastic Net Algorithm（CENA） is proposed in this paper. The algorithm has a new free energy function, and applies the maximum entropy principle. When the free energy reaches the global minimum, the clustering solution is obtained by the net. In this paper, a large number of random data points are tested. Experimental results show that the clustering results of CENA are stable. Compared with classical partitioning algorithms, CENA greatly improves the clustering quality. In general, the SED values of CENA are 20% lower than other classical partitioning algorithms.

Key words: cluster analysis, elastic net, maximum entropy, free energy