主成分分析(principal component analysis,PCA)是一种将高维数据投影到低维

数据的线性变换方法，这一方法的目的是寻找在最小均方意义下最能代表原始数据特征

的投影方向，用这些方向矢量表示数据。-Principal component analysis (PCA) is a kind of high dimensional data to the low dimension.The objective of this method is to find the characteristics of the original data in the least mean square sense.The projection direction is represented by the vector representation of the data.