sklearn之Ordinary Least Squares(普通最小二乘法)

sklearn中普通最小二乘法实现样例：

 1 import matplotlib.pyplot as plt
 2 import numpy as np
 3 from sklearn import datasets, linear_model
 4 
 5 diabetes = datasets.load_diabetes()
 6 diabetes_X = diabetes.data[:, np.newaxis, 2]
 7 
 8 diabetes_X_train = diabetes_X[:-20]
 9 diabetes_X_test = diabetes_X[-20:]
10 
11 diabetes_y_train = diabetes.target[:-20]
12 diabetes_y_test = diabetes.target[-20:]
13 
14 regr = linear_model.LinearRegression()
15 regr.fit(diabetes_X_train, diabetes_y_train)
16 
17 print('Coefficients: \n', regr.coef_)
18 print("Residual sum of squares: %.2f" % np.mean((regr.predict(diabetes_X_test) - diabetes_y_test) ** 2))
19 print('Variance score: %.2f' % regr.score(diabetes_X_test, diabetes_X_test))
20 
21 plt.scatter(diabetes_X_test, diabetes_y_test, color='black')
22 plt.plot(diabetes_X_test, regr.predict(diabetes_X_test), color='blue', linewidth=3)
23 
24 plt.xticks(())
25 plt.yticks(())
26 plt.show()

运行结果如下：

 

posted @ 2016-03-19 15:56  aclove  阅读(557)  评论(0)    收藏  举报