sklearn 的数据库

from sklearn import datasets
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
# 加载数据集 房价
loaded_data = datasets.load_boston()


data_X = loaded_data.data
data_y = loaded_data.target

# 选择模型
model = LinearRegression()
# 训练
model.fit(data_X,data_y)

print(model.predict(data_X[:4,:]))
print(data_y[:4])

# 生成100个例子，具有1个特征，1个标签，1个噪声
X,y = datasets.make_regression(n_samples=100,n_features=1,n_targets=1,noise=1)

plt.scatter(X,y)
plt.show()

结果
[30.00821269 25.0298606 30.5702317 28.60814055]
[24. 21.6 34.7 33.4]