基于遗传算法的无监督分层聚类

The 2003 Congress on Evolutionary Computation, 2003. CEC '03. Pub Date : 2003-12-08 DOI:10.1109/CEC.2003.1299776

W. A. Greene

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引用次数: 16

摘要

提出了一种无监督、增量、分层的聚类算法。该算法基于距离并创建质心。然后我们将进化力的力量与聚类算法结合起来，依靠好的聚类来进化出更好的聚类。我们将我们的方法应用于标准数据集，并得到了非常好的结果。最后，我们使用bagging方法对不同聚类试验的结果进行汇总，同样得到了非常好的结果。

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Unsupervised hierarchical clustering via a genetic algorithm

We present a clustering algorithm which is unsupervised, incremental, and hierarchical. The algorithm is distance-based and creates centroids. Then we combine the power of evolutionary forces with the clustering algorithm, counting on good clusterings to evolve to yet better ones. We apply our approach to standard data sets, and get very good results. Finally, we use bagging to pool the results of different clustering trials, and again get very good results.

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来源期刊

The 2003 Congress on Evolutionary Computation, 2003. CEC '03.

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