Abstract: Clustering validation is a key factor to the success of clustering.One of the approaches to validate the clustering results is clustering validation index.However，there is no general index for all kinds of data structures.A Dempster-Shafer，（D-S） evidence theory based ensemble method for multiple indices is proposed recently，named D-S theory based Validation method（DSV）.Experimental results and analysis on various synthetic data sets show that DSV outperforms single clustering validation index.

Key words: clustering validation, Dempster-Shafer（D-S） evidence theory, clustering validation index, cluster number

摘要： 针对现有研究中给出的聚类有效性指标不能有效评价不同结构数据集的聚类结果问题，提出一种使用多个有效性指标进行聚类评价的组合方法。引入D-S（Dempster-Shafer）证据理论对多个有效性指标结果进行集成，并得到最终的聚类评价结果。仿真实验和分析验证了该方法的可行性与有效性。

关键词: 聚类评价, D-S证据理论, 有效性指标, 聚类数