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.

Filename	Size	Update
pca.py	2057	2020-10-17
t10k-images-idx3-ubyte.gz	1648877	2018-10-10
t10k-labels-idx1-ubyte.gz	4542	2018-10-10
train-images-idx3-ubyte.gz	9912422	2018-10-10
train-labels-idx1-ubyte.gz	28881	2018-10-10

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