无监督聚类技术的研究

Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105) Pub Date : 2000-04-07 DOI:10.1109/SECON.2000.845446

H.S. Lee, N. H. Younan

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引用次数: 6

摘要

使用两个不能被任何超平面分离的清晰分离的三维数据集，比较几种无监督聚类技术的性能。结果表明，自组织特征映射可以在没有给定数据先验信息的情况下成功聚类数据集，而k-means和模糊k-means算法不能正确聚类。

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An investigation into unsupervised clustering techniques

The performance of several unsupervised clustering techniques is compared using two clearly separated 3-D data sets that are not separable by any hyperplane. The result shows that the self-organizing feature map can cluster data sets successfully without any prior information of given data while the k-means and the fuzzy k-means algorithm fail to cluster correctly.

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Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)

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