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一种基于聚类集成的无监督特征选择方法

, PP. 60-63

Keywords: 特征选择,无监督学习,集成学习

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Abstract:

提出了一种无监督的特征选择方法,其基本思想是利用聚类来指导特征选择,对于无类别标签的数据样本集,先进行聚类获得数据类标签,再利用ReliefF算法进行特征选择.采用聚类集成方法解决一些聚类结果的不稳定问题,最终特征选择结果通过多次特征选择综合得到.实验结果表明,该算法具有良好的特征选择性能,在去除无关或冗余特征后可进一步提高聚类质量.

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