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how should i choose random_state to got precise consequence
How should I read a file line-by-line in Python?TPOTClassifier producing errorsShould I specify a random_state in any classifier when doing a 10x10 StratifiedShuffleSplit?Scikit learn (Python 3.5): Do I need to import a library to make this work?Create model using one - hot encoding in KerasClassification with one file with entirely the training and another file with entirely testWhat should be the precise coordinates in basemap() for Europe?How to choose randomly in PythonWhich credentials should I choose and how?Training SVM with word2vector data
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty height:90px;width:728px;box-sizing:border-box;
When I use random_state=10. y_test[1] worked, but y_test[2 or 3 or...] did not.
So I tried to use other random_state, like 42 or 20, but upon changing, random_state.y_test[10] did not work too.
I'm not sure if the problem comes from y_test or from random_state.
And i wanna try to figure out why changing the value of random_state changes the precision of r2_score as well.
Thanks a lot
x = df[['mileage','engine_power','feature_1','feature_2','feature_3','feature_4','feature_5','feature_6','feature_7','feature_8','car_type']]
y = df['price']
x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=10)
lr =LinearRegression()
lr.fit(x_train,y_train)
predict_lr = lr.predict(x_test)
print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
print('real value y_test[2]:'+str(y_test[2])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
print('scort:',lr.score(x_test,y_test))
print('r2 score:',r2_score(y_test,predict_lr))
>>>real value y_test[1]:69700 predict:[12659.21124934]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-48-e556e02e9019> in <module>
3 predict_lr = lr.predict(x_test)
4 print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
----> 5 print('real value y_test[2]:'+str(y_test[5])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
6
7 print('scort:',lr.score(x_test,y_test))
KeyError: 5
python-3.x random-seed
edited Mar 29 at 4:44
kerwei
1,5191920
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
add a comment |
When I use random_state=10. y_test[1] worked, but y_test[2 or 3 or...] did not.
So I tried to use other random_state, like 42 or 20, but upon changing, random_state.y_test[10] did not work too.
I'm not sure if the problem comes from y_test or from random_state.
And i wanna try to figure out why changing the value of random_state changes the precision of r2_score as well.
Thanks a lot
x = df[['mileage','engine_power','feature_1','feature_2','feature_3','feature_4','feature_5','feature_6','feature_7','feature_8','car_type']]
y = df['price']
x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=10)
lr =LinearRegression()
lr.fit(x_train,y_train)
predict_lr = lr.predict(x_test)
print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
print('real value y_test[2]:'+str(y_test[2])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
print('scort:',lr.score(x_test,y_test))
print('r2 score:',r2_score(y_test,predict_lr))
>>>real value y_test[1]:69700 predict:[12659.21124934]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-48-e556e02e9019> in <module>
3 predict_lr = lr.predict(x_test)
4 print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
----> 5 print('real value y_test[2]:'+str(y_test[5])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
6
7 print('scort:',lr.score(x_test,y_test))
KeyError: 5
python-3.x random-seed
edited Mar 29 at 4:44
kerwei
1,5191920
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
add a comment |
When I use random_state=10. y_test[1] worked, but y_test[2 or 3 or...] did not.
So I tried to use other random_state, like 42 or 20, but upon changing, random_state.y_test[10] did not work too.
I'm not sure if the problem comes from y_test or from random_state.
And i wanna try to figure out why changing the value of random_state changes the precision of r2_score as well.
Thanks a lot
x = df[['mileage','engine_power','feature_1','feature_2','feature_3','feature_4','feature_5','feature_6','feature_7','feature_8','car_type']]
y = df['price']
x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=10)
lr =LinearRegression()
lr.fit(x_train,y_train)
predict_lr = lr.predict(x_test)
print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
print('real value y_test[2]:'+str(y_test[2])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
print('scort:',lr.score(x_test,y_test))
print('r2 score:',r2_score(y_test,predict_lr))
>>>real value y_test[1]:69700 predict:[12659.21124934]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-48-e556e02e9019> in <module>
3 predict_lr = lr.predict(x_test)
4 print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
----> 5 print('real value y_test[2]:'+str(y_test[5])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
6
7 print('scort:',lr.score(x_test,y_test))
KeyError: 5
python-3.x random-seed
edited Mar 29 at 4:44
kerwei
1,5191920
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
When I use random_state=10. y_test[1] worked, but y_test[2 or 3 or...] did not.
So I tried to use other random_state, like 42 or 20, but upon changing, random_state.y_test[10] did not work too.
I'm not sure if the problem comes from y_test or from random_state.
And i wanna try to figure out why changing the value of random_state changes the precision of r2_score as well.
Thanks a lot
x = df[['mileage','engine_power','feature_1','feature_2','feature_3','feature_4','feature_5','feature_6','feature_7','feature_8','car_type']]
y = df['price']
x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=10)
lr =LinearRegression()
lr.fit(x_train,y_train)
predict_lr = lr.predict(x_test)
print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
print('real value y_test[2]:'+str(y_test[2])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
print('scort:',lr.score(x_test,y_test))
print('r2 score:',r2_score(y_test,predict_lr))
>>>real value y_test[1]:69700 predict:[12659.21124934]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-48-e556e02e9019> in <module>
3 predict_lr = lr.predict(x_test)
4 print('real value y_test[1]:'+str(y_test[1])+' predict:'+str(lr.predict(x_test.iloc[[1],:])))
----> 5 print('real value y_test[2]:'+str(y_test[5])+' predict:'+str(lr.predict(x_test.iloc[[2],:])))
6
7 print('scort:',lr.score(x_test,y_test))
KeyError: 5
python-3.x random-seed
python-3.x random-seed
edited Mar 29 at 4:44
kerwei
1,5191920
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
edited Mar 29 at 4:44
kerwei
1,5191920
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
edited Mar 29 at 4:44
kerwei
1,5191920
edited Mar 29 at 4:44
kerwei
1,5191920
edited Mar 29 at 4:44
kerwei
1,5191920
1,5191920
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
asked Mar 24 at 10:04
韋辰姜韋辰姜
12
12
add a comment |
add a comment |
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