A novel clustering technique based on improved noising method

作者：Liu, Yongguo; Zhang, Wei; Zheng, Dong; Chen, Kefei

来源：10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Cuba, 2005-11-15 to 2005-11-18.

• Clustering algorithms
• Data sets
• Noising method

In this article, the clustering problem under the criterion of minimum sum of squares clustering is considered. It is known that this problem is a nonconvex program which possesses many locally optimal values, resulting that its solution often falls into these traps. To explore the proper result, a novel clustering technique based on improved noising method called INMC is developed, in which one-step DHB algorithm as the local improvement operation is integrated into the algorithm framework to fine-tune the clustering solution obtained in the process of iterations, Moreover, a new method for creating the neighboring solution of the noising method called mergence and partition operation is designed and analyzed in detail, Compared with two noising method based clustering algorithms recently reported, the proposed algorithm greatly improves the performance without the increase of the time complexity, which is extensively demonstrated for experimental data sets.

• 出版日期2005
• 单位南京大学; 上海交通大学; 电子科技大学; 重庆第二师范学院