Python predict_proba
I have a question on a classification problem in machine learning using the log_loss function in scikit learn.
from sklearn.ensemble import RandomForestClassifier
classifier = RandomForestClassifier()
classifier.fit(Xtrain, ytrain)
soft = classifier.predict_proba(Xtest)[:,1]
log_loss = log_loss(ytest, soft)
I would to compute the log loss but an error appears :
'numpy.float64' object is not callable
I think that this problem may come from the fact that there is some 0 in the vector soft. But I do know to solve this problem ?
s = 0
for x in soft :
if x == 0 :
s+=1
print(s)
>> 17729
Thanks in advance
python-3.x machine-learning scikit-learn
asked Nov 14 '18 at 11:46
user10651723user10651723
51
add a comment |
I have a question on a classification problem in machine learning using the log_loss function in scikit learn.
from sklearn.ensemble import RandomForestClassifier
classifier = RandomForestClassifier()
classifier.fit(Xtrain, ytrain)
soft = classifier.predict_proba(Xtest)[:,1]
log_loss = log_loss(ytest, soft)
I would to compute the log loss but an error appears :
'numpy.float64' object is not callable
I think that this problem may come from the fact that there is some 0 in the vector soft. But I do know to solve this problem ?
s = 0
for x in soft :
if x == 0 :
s+=1
print(s)
>> 17729
Thanks in advance
python-3.x machine-learning scikit-learn
asked Nov 14 '18 at 11:46
user10651723user10651723
51
Show the full stack trace of error and howlog_lossis imported?
– Vivek Kumar
Nov 14 '18 at 12:39
add a comment |
I have a question on a classification problem in machine learning using the log_loss function in scikit learn.
from sklearn.ensemble import RandomForestClassifier
classifier = RandomForestClassifier()
classifier.fit(Xtrain, ytrain)
soft = classifier.predict_proba(Xtest)[:,1]
log_loss = log_loss(ytest, soft)
I would to compute the log loss but an error appears :
'numpy.float64' object is not callable
I think that this problem may come from the fact that there is some 0 in the vector soft. But I do know to solve this problem ?
s = 0
for x in soft :
if x == 0 :
s+=1
print(s)
>> 17729
Thanks in advance
python-3.x machine-learning scikit-learn
asked Nov 14 '18 at 11:46
user10651723user10651723
51
I have a question on a classification problem in machine learning using the log_loss function in scikit learn.
from sklearn.ensemble import RandomForestClassifier
classifier = RandomForestClassifier()
classifier.fit(Xtrain, ytrain)
soft = classifier.predict_proba(Xtest)[:,1]
log_loss = log_loss(ytest, soft)
I would to compute the log loss but an error appears :
'numpy.float64' object is not callable
I think that this problem may come from the fact that there is some 0 in the vector soft. But I do know to solve this problem ?
s = 0
for x in soft :
if x == 0 :
s+=1
print(s)
>> 17729
Thanks in advance
python-3.x machine-learning scikit-learn
python-3.x machine-learning scikit-learn
asked Nov 14 '18 at 11:46
user10651723user10651723
51
asked Nov 14 '18 at 11:46
user10651723user10651723
51
asked Nov 14 '18 at 11:46
user10651723user10651723
51
asked Nov 14 '18 at 11:46
user10651723user10651723
51
asked Nov 14 '18 at 11:46
user10651723user10651723
51
51
Show the full stack trace of error and howlog_lossis imported?
– Vivek Kumar
Nov 14 '18 at 12:39
add a comment |
Show the full stack trace of error and howlog_lossis imported?
– Vivek Kumar
Nov 14 '18 at 12:39
Show the full stack trace of error and how
log_loss is imported?– Vivek Kumar
Nov 14 '18 at 12:39
Show the full stack trace of error and how
log_loss is imported?– Vivek Kumar
Nov 14 '18 at 12:39
add a comment |
1 Answer
1
active
oldest
votes
It appears as if your issue here is not really with the log_loss inputs, but just to do with your variable naming. Everything in python is an object and so in the line:
log_loss = log_loss(ytest, soft)
you assigned the answer, a number (of type numpy.float64), to the token log_loss. So your variable shadows the function. Then, subsequent calls, as if it were a function, fail.
from sklearn.metrics import log_loss
print(log_loss)
>>> <function log_loss at 0x7f9f692db1b8>
log_loss = log_loss(ytest, soft)
print(log_loss)
>>> 0.11895972559889094
log_loss = log_loss(ytest, soft)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-40-b423b2324b92> in <module>()
----> 1 log_loss = log_loss(ytest, soft)
TypeError: 'numpy.float64' object is not callable
Simplest resolution is not to call your variable log_loss, but more generally you might find some level of namespacing helps, e.g. instead of
from sklearn.metrics import log_loss
...
loss = log_loss(ytest, soft)
you could use
from sklearn import metrics
...
loss = metrics.log_loss(ytest, soft)
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
Thanks a lot!!!
– user10651723
Nov 14 '18 at 15:05
thanks but downvote? is your problem solved or do you need further help to get there?
– Bonlenfum
Nov 15 '18 at 11:02
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
It appears as if your issue here is not really with the log_loss inputs, but just to do with your variable naming. Everything in python is an object and so in the line:
log_loss = log_loss(ytest, soft)
you assigned the answer, a number (of type numpy.float64), to the token log_loss. So your variable shadows the function. Then, subsequent calls, as if it were a function, fail.
from sklearn.metrics import log_loss
print(log_loss)
>>> <function log_loss at 0x7f9f692db1b8>
log_loss = log_loss(ytest, soft)
print(log_loss)
>>> 0.11895972559889094
log_loss = log_loss(ytest, soft)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-40-b423b2324b92> in <module>()
----> 1 log_loss = log_loss(ytest, soft)
TypeError: 'numpy.float64' object is not callable
Simplest resolution is not to call your variable log_loss, but more generally you might find some level of namespacing helps, e.g. instead of
from sklearn.metrics import log_loss
...
loss = log_loss(ytest, soft)
you could use
from sklearn import metrics
...
loss = metrics.log_loss(ytest, soft)
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
Thanks a lot!!!
– user10651723
Nov 14 '18 at 15:05
thanks but downvote? is your problem solved or do you need further help to get there?
– Bonlenfum
Nov 15 '18 at 11:02
add a comment |
It appears as if your issue here is not really with the log_loss inputs, but just to do with your variable naming. Everything in python is an object and so in the line:
log_loss = log_loss(ytest, soft)
you assigned the answer, a number (of type numpy.float64), to the token log_loss. So your variable shadows the function. Then, subsequent calls, as if it were a function, fail.
from sklearn.metrics import log_loss
print(log_loss)
>>> <function log_loss at 0x7f9f692db1b8>
log_loss = log_loss(ytest, soft)
print(log_loss)
>>> 0.11895972559889094
log_loss = log_loss(ytest, soft)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-40-b423b2324b92> in <module>()
----> 1 log_loss = log_loss(ytest, soft)
TypeError: 'numpy.float64' object is not callable
Simplest resolution is not to call your variable log_loss, but more generally you might find some level of namespacing helps, e.g. instead of
from sklearn.metrics import log_loss
...
loss = log_loss(ytest, soft)
you could use
from sklearn import metrics
...
loss = metrics.log_loss(ytest, soft)
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
Thanks a lot!!!
– user10651723
Nov 14 '18 at 15:05
thanks but downvote? is your problem solved or do you need further help to get there?
– Bonlenfum
Nov 15 '18 at 11:02
add a comment |
It appears as if your issue here is not really with the log_loss inputs, but just to do with your variable naming. Everything in python is an object and so in the line:
log_loss = log_loss(ytest, soft)
you assigned the answer, a number (of type numpy.float64), to the token log_loss. So your variable shadows the function. Then, subsequent calls, as if it were a function, fail.
from sklearn.metrics import log_loss
print(log_loss)
>>> <function log_loss at 0x7f9f692db1b8>
log_loss = log_loss(ytest, soft)
print(log_loss)
>>> 0.11895972559889094
log_loss = log_loss(ytest, soft)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-40-b423b2324b92> in <module>()
----> 1 log_loss = log_loss(ytest, soft)
TypeError: 'numpy.float64' object is not callable
Simplest resolution is not to call your variable log_loss, but more generally you might find some level of namespacing helps, e.g. instead of
from sklearn.metrics import log_loss
...
loss = log_loss(ytest, soft)
you could use
from sklearn import metrics
...
loss = metrics.log_loss(ytest, soft)
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
It appears as if your issue here is not really with the log_loss inputs, but just to do with your variable naming. Everything in python is an object and so in the line:
log_loss = log_loss(ytest, soft)
you assigned the answer, a number (of type numpy.float64), to the token log_loss. So your variable shadows the function. Then, subsequent calls, as if it were a function, fail.
from sklearn.metrics import log_loss
print(log_loss)
>>> <function log_loss at 0x7f9f692db1b8>
log_loss = log_loss(ytest, soft)
print(log_loss)
>>> 0.11895972559889094
log_loss = log_loss(ytest, soft)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-40-b423b2324b92> in <module>()
----> 1 log_loss = log_loss(ytest, soft)
TypeError: 'numpy.float64' object is not callable
Simplest resolution is not to call your variable log_loss, but more generally you might find some level of namespacing helps, e.g. instead of
from sklearn.metrics import log_loss
...
loss = log_loss(ytest, soft)
you could use
from sklearn import metrics
...
loss = metrics.log_loss(ytest, soft)
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
answered Nov 14 '18 at 12:47
BonlenfumBonlenfum
11.3k13142
11.3k13142
Thanks a lot!!!
– user10651723
Nov 14 '18 at 15:05
thanks but downvote? is your problem solved or do you need further help to get there?
– Bonlenfum
Nov 15 '18 at 11:02
add a comment |
Thanks a lot!!!
– user10651723
Nov 14 '18 at 15:05
thanks but downvote? is your problem solved or do you need further help to get there?
– Bonlenfum
Nov 15 '18 at 11:02
Thanks a lot!!!
– user10651723
Nov 14 '18 at 15:05
Thanks a lot!!!
– user10651723
Nov 14 '18 at 15:05
thanks but downvote? is your problem solved or do you need further help to get there?
– Bonlenfum
Nov 15 '18 at 11:02
thanks but downvote? is your problem solved or do you need further help to get there?
– Bonlenfum
Nov 15 '18 at 11:02
add a comment |
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Show the full stack trace of error and how
log_lossis imported?– Vivek Kumar
Nov 14 '18 at 12:39