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特征加权优化软子空间聚类算法 被引量：2

A feature weighting optimized soft subspace clustering algorithm
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摘要 在聚类过程中结合簇内紧凑度信息和特征权值分布信息,对数据集的划分和各个簇类所在的子空间两方面进行优化。实验结果表明,该算法相比已有的软子空间聚类算法具有更好的聚类效果。 The within-class compactness data is combined with the feature weighting distribution data in the clustering process,and then both the data partition and each cluster are optimized in corresponding subspaces.Experimental studies demonstrate that the algorithm shows better features than the other soft subspace clustering algorithms.
作者 庄景晖
机构地区 漳州职业技术学院计算机工程系
出处 《长春工业大学学报》 CAS 2015年第4期414-420,共7页 Journal of Changchun University of Technology
基金 福建省教育厅科技项目(JB12329)
关键词 聚类 高维数据 软子空间 特征加权 clustering high-dimensional data soft subspace feature weighting.
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献14

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二级参考文献25

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长春工业大学学报
2015年 第4期

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