mnist

mnist.py

import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import load_digits
from sklearn.linear_model import LogisticRegression

digits = load_digits()


fig, ax = plt.subplots(2, 5)
plt.gray()		
a = 0
for row in ax:
	for col in row:
		col.title.set_text(digits.target[a])
		col.matshow(digits.images[a])
		col.axis('off')
		a += 1
plt.show()

logreg = LogisticRegression(c=1000, solver='saga', multi_class='multinomial')