Multiple_LinearRegression_Test2

 1 import csv
 2 import numpy as np
 3 from sklearn import datasets,linear_model
 4 
 5 with open("car_2.1.csv") as f:
 6     car_data = list(csv.reader(f))                #转换为list
 7     data_X = [row[:5] for row in car_data[:-1]]  #变量x
 8     data_Y = [row[-1] for row in car_data[:-1]]  #值y
 9     xPred = car_data[-1]                         #测试数据
10     f.close()
11 regression = linear_model.LinearRegression()     #调用回归函数
12 regression.fit(data_X,data_Y)
13 xPred = np.array(xPred[:-1],dtype=float)                     #去掉最后的y值,并转换为数组类型
14 print(regression.coef_)                          #各个变量前的系数
15 print(regression.intercept_)                     #获取截距
16 
17 #注意：reshape(1,-1)是为了让矩阵能够对齐
18 yPred = regression.predict(xPred.reshape(1, -1))                #测试数据
19 print("结果为：",yPred)