[数据挖掘/数据仓库] PCA+mnist

基于python，利用主成分分析（PCA）和K近邻算法（KNN）在MNIST手写数据集上进行了分类。 经过PCA降维，最终的KNN在100维的特征空间实现了超过97%的分类精度。
Based on python, it uses principal component analysis (PCA) and K nearest neighbor algorithm (KNN) to classify on the MNIST handwritten data set. After PCA dimensionality reduction, the final KNN achieved a classification accuracy of over 97% in a 100-dimensional feature space. (2020-10-27, Python, 11328KB, 下载9次)