无监督数据聚类环境下统计模糊隶属度模型的特征

Proceedings of 1994 Workshop on Information Theory and Statistics Pub Date : 1994-10-27 DOI:10.1109/WITS.1994.513926

L. Talbot, H. Tolley, B. Talbot, H.D. Mecham

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引用次数: 0

摘要

我们阐明了Woodbury(1974)统计模糊隶属度(GoM)模型在无监督聚类领域中的地位。该模型的实现不仅可以操作多变量分类数据，还可以操作排列或编码的数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Characteristics of a statistical fuzzy grade-of-membership model in the context of unsupervised data clustering

We have elucidated the position of Woodbury's (1974) statistical fuzzy grade-of-membership (GoM) model in the unsupervised clustering domain. This implementation of the model is shown to operate not only on multivariate categorical data, but on permuted, or encoded, data as well.

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Proceedings of 1994 Workshop on Information Theory and Statistics

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