This paper deals with the multivariate vector analysis of quality data by geometric transformation, rotating coordinates and computation of the principal component of initial variables.
本文讨论多元质量数据的矢量分析方法，几何变换，坐标旋转和初始变量的主分量计算不同变量的主分量值。
Through support vector machine algorithms for gene expression data classification training, SVMs provide a effective way for analysis of gene expression data.
通过支持向量机训练算法对基因表达数据进行分类训练，为分析基因数据提供有效的手段。
This article focuses on the method in improved vector generators and the data analysis of results.
重点介绍了改进型矢量产生器的方法和数据结果分析。
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