from __future__ import print_function
from sklearn import datasets
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
loaded_data = datasets.load_boston()
data_X = loaded_data.data
data_y = loaded_data.target
model = LinearRegression()
model.fit(data_X, data_y)
print(model.predict(data_X[:4, :]))
print(data_y[:4])
# n_samples=100表示100個樣本點，n_features=1表示1個特徵
# n_targets=1表示1個目標，noise=10噪音等級爲10
X, y = datasets.make_regression(n_samples=100, n_features=1, n_targets=1, noise=10)
# scatter表示用點描述
plt.scatter(X, y)
plt.show()
