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本文提出一种利用平行坐标图的多元信息表示对主成分分析特征提取方法进行优化的分类技术。
A novel method for optimizing the principle component analysis in feature extraction is proposed, which making use of parallel coordinate plot for graphical presentation of multivariate information.
主成分分析属多元统计方法，正逐步成为控制领域中一种重要的数据处理方法，用于生产监测和质量控制。
Principle component analysis is based on multi-statistics method, and turning into an important way to proceed data for production monitoring and quality control.
到目前为止，最重要的原因为执行一个主成分分析(PCA)是使用它当作一个工具，用于筛选的多元数据。
By far, the most important reason for performing a principal components analysis (PCA) is to use it as a tool for screening multivariate data.
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