【作者】 任鸿； 郑岩； 曲昭伟； 邓芳；

【Author】 REN Hong, ZHENG Yan, QU Zhao-wei, DENG Fang ( School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China; Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China; Research Center of Electronic Commerce, Beijing University of Posts and Telecommunications, Beijing 100876, China)

【机构】 北京邮电大学电子工程学院； 北京邮电大学智能通信软件与多媒体北京市重点实验室； 北京邮电大学电子商务中心；

【摘要】 在对现有各种聚类有效性函数进行深入分析的基础上,提出了一种改进的聚类有效性函数,通过引入模拟退火机制,以获得最佳聚类结果．与其他经典的聚类有效性函数相比,改进后的聚类有效性函数一方面避免了单调性,另一方面又与数据集合本身的特征相关．仿真实验表明了其有效性．更多还原

【Abstract】 In order to obtain the optimal clustering result, an improved method is proposed by incorporating the simulated annealing mechanism based on analyzing the existing clustering validity functions. Comparing with the typical clustering validity functions, the advantages of this improved method will avoid the mono-tonicity and associate with the characteristics of the dataset. Experimental results show its effectiveness.更多还原