神经网络训练手写字集

import matplotlib.pyplot as plt
from sklearn import neural_network
from sklearn.datasets import load_digits# 加载数据集
digits = load_digits()
X = digits.data
Y = digits.target
# 过拟合：增加训练样本
train_x = X[:-100]; test_x = X[-100:]
train_y = Y[:-100]; test_y = Y[-100:]def mlpclassifier_digits():classifier = neural_network.MLPClassifier(activation='logistic',max_iter=10000, hidden_layer_sizes=(100,))classifier.fit(train_x, train_y)train_score = classifier.score(train_x, train_y)test_score = classifier.score(test_x, test_y)print(train_score)print(test_score)tes=test_y[:100]print(tes)res = classifier.predict(test_x[:100])print(res)fig = plt.figure(figsize=(6, 6))for i in range(100):ax = fig.add_subplot(10, 10, i + 1, xticks=[], yticks=[])ax.imshow(test_x.reshape(-1, 8, 8)[i], cmap=plt.cm.binary, interpolation='nearest')if tes[i] == res[i]:ax.text(0, 7, str(res[i]), color="green")else:ax.text(0, 7, str(res[i]), color='red')plt.show()mlpclassifier_digits()

效果图：

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