How to silence all sklearn warning
1
I am using F1_score metrics in sklearn. For some training data sets, the total number of y=1(rare case) sets is zero, the F1_score is zero,which is normal. But the sklearn gives the following warning:
"UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 due to no predicted samples".
Does anyone know how to silence this warning? and in general could we silence all kinds of warnings in sklearn ?
python scikit-learn
asked Dec 29 '18 at 8:36
sauntersaunter
85
add a comment |
1
I am using F1_score metrics in sklearn. For some training data sets, the total number of y=1(rare case) sets is zero, the F1_score is zero,which is normal. But the sklearn gives the following warning:
"UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 due to no predicted samples".
Does anyone know how to silence this warning? and in general could we silence all kinds of warnings in sklearn ?
python scikit-learn
asked Dec 29 '18 at 8:36
sauntersaunter
85
The accepted answer here seems to have the information you are interested in: stackoverflow.com/questions/43162506/…
– Jason Baumgartner
Dec 29 '18 at 8:40
Possible duplicate of UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples
– AI_Learning
Dec 29 '18 at 16:07
I checked all, but not able to find the one I wanted
– saunter
Jan 2 at 2:48
add a comment |
1
1
1
I am using F1_score metrics in sklearn. For some training data sets, the total number of y=1(rare case) sets is zero, the F1_score is zero,which is normal. But the sklearn gives the following warning:
"UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 due to no predicted samples".
Does anyone know how to silence this warning? and in general could we silence all kinds of warnings in sklearn ?
python scikit-learn
asked Dec 29 '18 at 8:36
sauntersaunter
85
I am using F1_score metrics in sklearn. For some training data sets, the total number of y=1(rare case) sets is zero, the F1_score is zero,which is normal. But the sklearn gives the following warning:
"UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 due to no predicted samples".
Does anyone know how to silence this warning? and in general could we silence all kinds of warnings in sklearn ?
python scikit-learn
python scikit-learn
asked Dec 29 '18 at 8:36
sauntersaunter
85
asked Dec 29 '18 at 8:36
sauntersaunter
85
edited Jan 2 at 2:42
saunter
asked Dec 29 '18 at 8:36
sauntersaunter
85
asked Dec 29 '18 at 8:36
sauntersaunter
85
asked Dec 29 '18 at 8:36
sauntersaunter
85
85
The accepted answer here seems to have the information you are interested in: stackoverflow.com/questions/43162506/…
– Jason Baumgartner
Dec 29 '18 at 8:40
Possible duplicate of UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples
– AI_Learning
Dec 29 '18 at 16:07
I checked all, but not able to find the one I wanted
– saunter
Jan 2 at 2:48
add a comment |
The accepted answer here seems to have the information you are interested in: stackoverflow.com/questions/43162506/…
– Jason Baumgartner
Dec 29 '18 at 8:40
Possible duplicate of UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples
– AI_Learning
Dec 29 '18 at 16:07
I checked all, but not able to find the one I wanted
– saunter
Jan 2 at 2:48
The accepted answer here seems to have the information you are interested in: stackoverflow.com/questions/43162506/…
– Jason Baumgartner
Dec 29 '18 at 8:40
The accepted answer here seems to have the information you are interested in: stackoverflow.com/questions/43162506/…
– Jason Baumgartner
Dec 29 '18 at 8:40
Possible duplicate of UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples
– AI_Learning
Dec 29 '18 at 16:07
Possible duplicate of UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples
– AI_Learning
Dec 29 '18 at 16:07
I checked all, but not able to find the one I wanted
– saunter
Jan 2 at 2:48
I checked all, but not able to find the one I wanted
– saunter
Jan 2 at 2:48
add a comment |
1 Answer
1
active
oldest
votes
3
You can easily ignore the warnings with the help of warnings module in Python like this.
import warnings
warnings.filterwarnings('ignore')
For example,
from sklearn.metrics import f1_score
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This will throw warning. To avoid that use,
from sklearn.metrics import f1_score
import warnings
warnings.filterwarnings('ignore')
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This wont show the warning.
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
Thanks for your info. Actually I have the line "warnings.filterwarnings('ignore')" at the beginning of my code, but still the warning pops out. The reason I guess this "ignore" line only controls warnings of python modules not sklearn ones. In your example, you probably need to exchange y and yhat in the f1_score function to see the effect since the first argument is the ytrue and the second is ypred
– saunter
Jan 2 at 2:47
@saunter, I have tried both ways. I am not getting any warning in my Machine. Withoutwarnings.filterwarnings('ignore')I am getting the warning, but with that code I am not getting any warnings.
– Sreeram TP
Jan 2 at 9:38
You are correct. I tested it again,it worked.
– saunter
Jan 3 at 1:36
Nice to hear it helped.
– Sreeram TP
Jan 3 at 5:08
add a comment |
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1 Answer
1
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oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
3
You can easily ignore the warnings with the help of warnings module in Python like this.
import warnings
warnings.filterwarnings('ignore')
For example,
from sklearn.metrics import f1_score
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This will throw warning. To avoid that use,
from sklearn.metrics import f1_score
import warnings
warnings.filterwarnings('ignore')
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This wont show the warning.
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
Thanks for your info. Actually I have the line "warnings.filterwarnings('ignore')" at the beginning of my code, but still the warning pops out. The reason I guess this "ignore" line only controls warnings of python modules not sklearn ones. In your example, you probably need to exchange y and yhat in the f1_score function to see the effect since the first argument is the ytrue and the second is ypred
– saunter
Jan 2 at 2:47
@saunter, I have tried both ways. I am not getting any warning in my Machine. Withoutwarnings.filterwarnings('ignore')I am getting the warning, but with that code I am not getting any warnings.
– Sreeram TP
Jan 2 at 9:38
You are correct. I tested it again,it worked.
– saunter
Jan 3 at 1:36
Nice to hear it helped.
– Sreeram TP
Jan 3 at 5:08
add a comment |
3
You can easily ignore the warnings with the help of warnings module in Python like this.
import warnings
warnings.filterwarnings('ignore')
For example,
from sklearn.metrics import f1_score
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This will throw warning. To avoid that use,
from sklearn.metrics import f1_score
import warnings
warnings.filterwarnings('ignore')
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This wont show the warning.
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
Thanks for your info. Actually I have the line "warnings.filterwarnings('ignore')" at the beginning of my code, but still the warning pops out. The reason I guess this "ignore" line only controls warnings of python modules not sklearn ones. In your example, you probably need to exchange y and yhat in the f1_score function to see the effect since the first argument is the ytrue and the second is ypred
– saunter
Jan 2 at 2:47
@saunter, I have tried both ways. I am not getting any warning in my Machine. Withoutwarnings.filterwarnings('ignore')I am getting the warning, but with that code I am not getting any warnings.
– Sreeram TP
Jan 2 at 9:38
You are correct. I tested it again,it worked.
– saunter
Jan 3 at 1:36
Nice to hear it helped.
– Sreeram TP
Jan 3 at 5:08
add a comment |
3
3
3
You can easily ignore the warnings with the help of warnings module in Python like this.
import warnings
warnings.filterwarnings('ignore')
For example,
from sklearn.metrics import f1_score
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This will throw warning. To avoid that use,
from sklearn.metrics import f1_score
import warnings
warnings.filterwarnings('ignore')
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This wont show the warning.
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
You can easily ignore the warnings with the help of warnings module in Python like this.
import warnings
warnings.filterwarnings('ignore')
For example,
from sklearn.metrics import f1_score
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This will throw warning. To avoid that use,
from sklearn.metrics import f1_score
import warnings
warnings.filterwarnings('ignore')
yhat = [0] * 100
y = [0] * 90 + [1] * 10
print(f1_score(y, yhat))
This wont show the warning.
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
edited Jan 2 at 9:39
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
answered Dec 29 '18 at 9:22
Sreeram TPSreeram TP
2,70421134
2,70421134
Thanks for your info. Actually I have the line "warnings.filterwarnings('ignore')" at the beginning of my code, but still the warning pops out. The reason I guess this "ignore" line only controls warnings of python modules not sklearn ones. In your example, you probably need to exchange y and yhat in the f1_score function to see the effect since the first argument is the ytrue and the second is ypred
– saunter
Jan 2 at 2:47
@saunter, I have tried both ways. I am not getting any warning in my Machine. Withoutwarnings.filterwarnings('ignore')I am getting the warning, but with that code I am not getting any warnings.
– Sreeram TP
Jan 2 at 9:38
You are correct. I tested it again,it worked.
– saunter
Jan 3 at 1:36
Nice to hear it helped.
– Sreeram TP
Jan 3 at 5:08
add a comment |
Thanks for your info. Actually I have the line "warnings.filterwarnings('ignore')" at the beginning of my code, but still the warning pops out. The reason I guess this "ignore" line only controls warnings of python modules not sklearn ones. In your example, you probably need to exchange y and yhat in the f1_score function to see the effect since the first argument is the ytrue and the second is ypred
– saunter
Jan 2 at 2:47
@saunter, I have tried both ways. I am not getting any warning in my Machine. Withoutwarnings.filterwarnings('ignore')I am getting the warning, but with that code I am not getting any warnings.
– Sreeram TP
Jan 2 at 9:38
You are correct. I tested it again,it worked.
– saunter
Jan 3 at 1:36
Nice to hear it helped.
– Sreeram TP
Jan 3 at 5:08
Thanks for your info. Actually I have the line "warnings.filterwarnings('ignore')" at the beginning of my code, but still the warning pops out. The reason I guess this "ignore" line only controls warnings of python modules not sklearn ones. In your example, you probably need to exchange y and yhat in the f1_score function to see the effect since the first argument is the ytrue and the second is ypred
– saunter
Jan 2 at 2:47
Thanks for your info. Actually I have the line "warnings.filterwarnings('ignore')" at the beginning of my code, but still the warning pops out. The reason I guess this "ignore" line only controls warnings of python modules not sklearn ones. In your example, you probably need to exchange y and yhat in the f1_score function to see the effect since the first argument is the ytrue and the second is ypred
– saunter
Jan 2 at 2:47
@saunter, I have tried both ways. I am not getting any warning in my Machine. Without
warnings.filterwarnings('ignore') I am getting the warning, but with that code I am not getting any warnings.– Sreeram TP
Jan 2 at 9:38
@saunter, I have tried both ways. I am not getting any warning in my Machine. Without
warnings.filterwarnings('ignore') I am getting the warning, but with that code I am not getting any warnings.– Sreeram TP
Jan 2 at 9:38
You are correct. I tested it again,it worked.
– saunter
Jan 3 at 1:36
You are correct. I tested it again,it worked.
– saunter
Jan 3 at 1:36
Nice to hear it helped.
– Sreeram TP
Jan 3 at 5:08
Nice to hear it helped.
– Sreeram TP
Jan 3 at 5:08
add a comment |
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The accepted answer here seems to have the information you are interested in: stackoverflow.com/questions/43162506/…
– Jason Baumgartner
Dec 29 '18 at 8:40
Possible duplicate of UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples
– AI_Learning
Dec 29 '18 at 16:07
I checked all, but not able to find the one I wanted
– saunter
Jan 2 at 2:48