1、导入sklearn数据库

2、导入数据库的数据

3、数据分析

def linear_model1():

data=load_boston()

print(data.data)

print(data.target)

x_train, x_test, y_train, y_test = train_test_split(data.data, data.target,random_state=22)

transfer = StandardScaler()

x_train = transfer.fit_transform(x_train)

x_test = transfer.fit_transform(x_test)

estimator = LinearRegression()

estimator.fit(x_train, y_train)

y_predict = estimator.predict(x_test)

print("预测值为:\n", y_predict)

print("模型中的系数为:\n", estimator.coef_)

print("模型中的偏置为:\n", estimator.intercept_)

error = mean_squared_error(y_test, y_predict)

print("误差为:\n", error)

return None

4、输出结果

学号：202113430104万熙