In [9]:

    

import pandas as pd
import os
PATH = os.getcwd()
%matplotlib inline


    

In [10]:

    

df1 = pd.read_csv(f'{PATH}\\AV_Stud\\xgb_0.7.csv')
df2 = pd.read_csv(f'{PATH}\\AV_Stud\\xgb_0.4&xgb_0.3.csv')


    

In [11]:

    

df1.head()


    

    
Out[11]:







  

    

      

      
id
      
is_pass
    
  
  

    

      
0
      
1626_45
      
0.507105
    
    

      
1
      
11020_130
      
0.995746
    
    

      
2
      
12652_146
      
0.540914
    
    

      
3
      
7038_72
      
0.006350
    
    

      
4
      
888_71
      
0.212951
    
  

In [12]:

    

df2.head()


    

    
Out[12]:







  

    

      

      
id
      
is_pass
    
  
  

    

      
0
      
1626_45
      
0.488407
    
    

      
1
      
11020_130
      
0.994501
    
    

      
2
      
12652_146
      
0.595252
    
    

      
3
      
7038_72
      
0.010464
    
    

      
4
      
888_71
      
0.346809
    
  

In [17]:

    

df2['is_pass'] = df1['is_pass'] * .85 + df2['is_pass'] * .15


    

In [18]:

    

df2.to_csv(f'{PATH}\\AV_Stud\\xgb_0.4&xgb_0.3&xgb_0.7.csv', index = False)


    

In [ ]:

    

xgb_0.4&xgb_0.3&xgb_0.7.csv'


    

In [ ]:

    




    

In [26]:

    

df1 = pd.read_csv(f'{PATH}\\AV_Stud\\xgb_0.4&xgb_0.3&xgb_0.7.csv')
df2 = pd.read_csv(f'{PATH}\\AV_Stud\\xgb_0.4&xgb_0.3&xgb_0.7(&xgb_0.4&xgb_0.3).csv')


    

In [24]:

    

df2['is_pass'] = df2['is_pass'] * .85 + .15 * df1['is_pass']


    

In [25]:

    

df2.to_csv(f'{PATH}\\AV_Stud\\xgb_0.4&xgb_0.3&xgb_0.7(&xgb_0.4&xgb_0.3)_v1.csv', index = False)


    

In [29]:

    

df2['is_pass'].quantile(q=[.1,.2,.3,.4,.5,.6,.7,.8,.9])


    

    
Out[29]:





0.1    0.177586
0.2    0.342803
0.3    0.494333
0.4    0.633314
0.5    0.747091
0.6    0.834378
0.7    0.898935
0.8    0.945139
0.9    0.977810
Name: is_pass, dtype: float64

In [30]:

    

max(df2['is_pass'])


    

    
Out[30]:





0.99963813462108364

In [31]:

    

import numpy as np


    

In [34]:

    

preds = np.where(df2['is_pass']>=.977, .999, df2['is_pass'])


    

In [35]:

    

df2['is_pass'] = preds


    

In [36]:

    

df2.to_csv(f'{PATH}\\AV_Stud\\mixed_.977_to_.999.csv',index=False)


    

In [ ]: