sklearn常用数据的使用

from sklearn import datasets
from sklearn.linear_model import LinearRegression
#加载数据
loaded_data = datasets.load_boston()
data_X = loaded_data.data
data_Y = loaded_data.target
#是否需要对数据进行拆分
#定义模型
model = LinearRegression()
#训练
model.fit(data_X,data_Y)

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

from sklearn import datasets
import matplotlib.pyplot as plt

X,Y = datasets.make_regression(n_samples=100,n_features=1,n_targets=1,noise=1)
plt.scatter(X,Y)
plt.show()