1·Based on the definition of PCA, it essentially owns classification ability.
根据主成分分析的定义,它本质上具有分类的能力。
2·Proposed a Band Selection algorithm based on Segmented PCA.
提出了一种基于分段主成分分析的波段选择算法。
3·Using a Parallel plot, PCA and Nonparametric Scatterplot Matrix to Study the Evolution in Time of a Multivariate Industrial Process.
运用平行图、主成分分析和非参数散点图矩阵等方法,研究多变量工业流程在时域内的变化规律。
4·To analysis the sample data space by PCA can assume that it can lower the dimension of high variant space and eliminate the relativity of sample data.
通过对样本数据空间的主成分分析,能够保证在信息损失最少的情况下,对高维变量空间进行降维处理,减少样本数据间的相关性。
5·Radix salviae miltiorrhizae: by PCA, clustering result is associated with regions;
丹参:经过主成分分析,聚类结果与地理位置有一定的相关性;