Abstract：To improve the clustering performance, an incomplete data imputation clustering algorithm based on difference of convex functions programming (DCP) is proposed. DCP is applied to optimize the kernel-based fuzzy C-means objective function, and the alternative optimization process for DCP clustering and missing completion is given. The convergence of the alternating optimization is proved theoretically. Experiments show the superiority of the proposed algorithm in missing completion and clustering performance.
贺丹,陈松灿. 基于凸差规划的不完整数据填充聚类[J]. 模式识别与人工智能, 2017, 30(1): 81-88.
HE Dan, CHEN Songcan. Incomplete Data Imputation Clustering Based on Difference of Convex Functions Programming. , 2017, 30(1): 81-88.
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