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基于特征加权的模糊聚类算法研究
A Feature Weighted Fuzzy Clustering Algorithm
【摘要】 模糊聚类分析是非监督模式分类的一个分支,在模式识别中有着重要的地位。在FCM算法中,考虑到样本矢量中各维特征对模式分类的不同影响,本文引入一种基于特征加权的模糊聚类算法,该算法考虑了各维特征对分类的贡献不同,从而对数据进行了更有效的分类。
【Abstract】 Fuzzy clustering analysis is a branch of unsupervised pattern classification, and plays an important role in fuzzy pattern recognition. In the Fuzzy c-Means algorithm, considering the particular contributions of different feature, a feature weight fuzzy clustering algorithm is introduced in this paper. By weighting the features of samples, better classification results can be achieved.
- 【文献出处】 北京电子科技学院学报 ,Journal of Beijing Electronic Science and Technology Institute , 编辑部邮箱 ,2007年02期
- 【分类号】TP301.6
- 【被引频次】29
- 【下载频次】567