Python实用线性回归算法

 1 print('=====您好！这里是简单线性回归方程求解模型=====')
 2 num = int(input('请输入您需要操作的样本对数'))
 3 # 接收自变量的List
 4 xList = []
 5 # 接收因变量的List
 6 yList = []
 7 
 8 for i in range(num):
 9     x = int(input('自变量：'))
10     xList.append(x)
11     y = int(input('因变量：'))
12     yList.append(y)
13     print()
14 # X表示自变量的均值
15 # Y表示因变量的均值
16 X = sum(xList)/len(xList)
17 Y = sum(yList)/len(yList)
18 
19 totalX = 0
20 totalX_Y = 0
21 SST = 0    # 总的平方和
22 SSE = 0    # 误差平方和
23 
24 for i in range(num):
25     totalX_Y += (xList[i]-X)*(yList[i]-Y)
26     totalX += (xList[i]-X)**2
27     SST += (yList[i]-Y)**2
28 
29 b1 = totalX_Y/totalX
30 b0 = Y-b1*X
31 
32 for i in range(num):
33     # 求因变量的预测值
34     yi = b0 + b1*xList[i]
35     SSE += (yList[i]-yi)**2
36 
37 r2 = 1 - SSE/SST
38 
39 print('估计的回归方程：y={0}x+{1}'.format(b1,b0))
40 print('判定系数：{0}'.format(r2))
作者李安国
爱我没结果！