1.前言
sklearn 神经网络，进行多分类，数字识别。
2.python 代码
（1）数据集用的 sklearn 自带，数字 0~9 分类
（2）采用 MLPClassifier
（3）执行代码如下 multi_class_nn.py:
from sklearn.neural_network import MLPClassifier
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt
# 测试集，画图对预测值和实际值进行比较
def test_validate(x_test, y_test, y_predict, classifier):
x = range(len(y_test))
plt.plot(x, y_test, "ro", markersize=5, zorder=3, label=u"true_v")
plt.plot(x, y_predict, "go", markersize=8, zorder=2,
label=u"predict_v,$R$=%.3f" % classifier.score(x_test, y_test))
plt.legend(loc="upper left")
plt.xlabel("number")
plt.ylabel("true?")
plt.show()
# 神经网络数字分类
def multi_class_nn():
digits = datasets.load_digits()
x = digits['data']
y = digits['target']
