一种基于吸引领导者的非对称邻近聚类方法

2007 International Conference on Signal Processing, Communications and Networking Pub Date : 2007-11-05 DOI:10.1109/ICSCN.2007.350691

B. B. Kiranagi, D. S. Guru

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引用次数: 1

摘要

本文讨论了符号数据间非对称接近的重要性，提出了一种新的聚类算法。该算法直接作用于非对称邻近矩阵，并基于面向领导者的增量方法。为了研究所提出方法的有效性，在标准符号数据集上进行了实验

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An Attractive Leader Approach Based Clustering for Non-Symmetric Proximity

In this paper, the importance of non-symmetric proximity between symbolic data is discussed and a new algorithm for clustering is proposed. The proposed algorithm works directly on the non-symmetric proximity matrices and is based on the leader oriented incremental approach. Experiments on the standard symbolic data sets have been conducted in order to study the efficacy of the proposed methodology

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来源期刊

2007 International Conference on Signal Processing, Communications and Networking

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