第1关：神经网络分类器

from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import pandas as pd

def test_m():
    data_url = "/data/workspace/myshixun/home/diabetes.csv"
    df = pd.read_csv(data_url)
    Xa = df.iloc[:,0:8]
    ya = df.iloc[:,8]
    X_train_1, X_test_1, y_train_1, y_test_1 = train_test_split(Xa, ya, test_size=0.2, random_state=0)
    
    # 利用MLPClassifier函数制作神经网络
    # 使用solver='sgd'，10个隐藏层，5个输出层，随机数种子为1
    clf = MLPClassifier(solver='sgd', hidden_layer_sizes=(10, 5), random_state=1)
    clf.fit(X_train_1, y_train_1)

    return accuracy_score(y_train_1, clf.predict(X_train_1)), accuracy_score(y_test_1, clf.predict(X_test_1))

# 测试函数
train_accuracy, test_accuracy = test_m()
print("训练集准确率：", train_accuracy)
print("测试集准确率：", test_accuracy)