sklearn的数据训练和评估1

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sklearn的数据训练和评估1

1. import matplotlib.pyplot as plt
   
2. import pandas as pd
   
3. from collections import OrderedDict
   
4. from sklearn.linear_model import LinearRegression
   
5. from sklearn.model_selection import train_test_split
   
6. 
   
7. examDict = {'学习时间':[0.5,0.75,1,1.25,1.5,1.75,1.75,2,2.25,2.5,2.75,3,
   
8.                     3.25,3.5,4,4.25,4.5,4.75,5,5.0],
   
9.             '分数':[10,22,13,43,20,22,33,50,62,48,55,75,62,
   
10.                   73,81,76,64,82,90,93]
    
11.             }
    
12. examOrderedDict = OrderedDict(examDict)
    
13. examDf = pd.DataFrame(examOrderedDict)
    
14. # examDf.head()
    
15. exam_X = examDf.loc[:,'学习时间']
    
16. exam_y = examDf.loc[:,'分数']
    
17. plt.scatter(exam_X,exam_y,color='b',label='exam data')
    
18. plt.legend(loc=2)
    
19. plt.xlabel('Hours')
    
20. plt.ylabel('Score')
    
21. plt.show()

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