一种新的特征提取方法——类别非局保留投影

A New Method for Feature Extraction ——Class-Wise Non-Locality Preserving Projection

  • 摘要: 针对类别保局投影基于类内散度的特点,提出了一种基于类间散度的特征提取方法——类别非局保留投影. 利用Matlab软件对类别保局投影、主分量分析和类别非局保留投影进行了可视化效果和聚类识别率的比较、分析. 结果表明,在类间信息起主导作用的基因表达数据分类任务中,类别非局保留投影比类别保局投影能获得更好的分类特征. 因此类别非局保留投影更适合于类间信息其主导作用的分类任务.

     

    Abstract: In contrast to the existing class-wise locality preserving projection (CLPP), a technique based on the characterization of the inner-cluster scatter,a novel feature extraction method for gene expression data, called class-wise non-locality preserving projection (CNLPP), is proposed, which is based on the characterization of the inter-cluster scatter. The idea of CNLPP was realized with Matlab to show the effectiveness of visualization and clustering recognition on gene expression data after feature extraction and was compared with PCA, CLPP. The results indicate that CNLPP is more effective for feature extraction than CLPP when the inter-cluster information plays a dominant role in discrimination. The new method is more suitable for use in the task of classification when the inter-cluster information plays a dominant role.

     

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