聚类分析
趋同(经济学)
数学
子序列
算法
模糊聚类
模糊逻辑
班级(哲学)
计算机科学
数学优化
人工智能
标识
DOI:10.1109/tpami.1980.4766964
摘要
In this paper the convergence of a class of clustering procedures, popularly known as the fuzzy ISODATA algorithms, is established. The theory of Zangwill is used to prove that arbitrary sequences generated by these (Picard iteration) procedures always terminates at a local minimum, or at worst, always contains a subsequence which converges to a local minimum of the generalized least squares objective functional which defines the problem.
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