mnist手写数字识别(神经网络)

import numpy as np

from sklearn.neural_network import MLPClassifier

path = 'mnist.npz'

f = np.load(path)

X_train , y_train = f['x_train'], f['y_train']

X_test , y_test = f['x_test'], f['y_test']

X_train = X_train.astype('float32')

X_test = X_test.astype('float32')

X_train /= 255.

X_test /= 255.

X_train = X_train.reshape(60000,784)

X_test = X_test.reshape(10000,784)

mlp = MLPClassifier(hidden_layer_sizes=(100,100,100))

mlp.fit(X_train,y_train)

print('Training set score: %f' % mlp.score(X_train,y_train))

print('Test set score: %f' % mlp.score(X_test,y_test))

# print(X_train[0])

'''

print(X_train.shape)

print(y_train.shape)

print(X_test.shape)

print(y_test.shape)

'''