说明：  《机器学习》课上的作业，PCA和LDA降维，尽管网上很多，但很少注释，另外细节上也没注意。这里有很详细的注释。另外还附上一个Naive贝叶斯分类器，大家可以作比较。附带的图像包是OLR人脸。ReducedDim为想要提取的特征数，不是百分比！
(" Machine learning" classes on the homework, PCA and LDA dimensionality reduction, even though a lot of online, but few notes, on the other did not pay attention to details. Here there is a very detailed notes. In addition, attach a Naive Bayesian classifier, we can compare. Fringe image packages are OLR people face. ReducedDim you want to extract the characteristics of a few, not a percentage!)