[scikit-learn] SVM-RFE with scoring = 'f1'

[Malik Yousef]

Thanks for your reply.
How I can set the name of the positive class in LinearSVC() for a two-class
problem that when using the prediction then I will get positive scores fro
that positive class?

Malik
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*Prof. Malik Yousef , Associate Professor                           *
*Zefat Academic College , Department of Information System  *
Home Page:
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On Thu, Aug 1, 2019 at 8:43 PM Joel Nothman <joel.nothman at gmail.com> wrote:

> Or use scoring=make_scorer(f1_score, pos_label='n.pre')
>
> On Fri, 2 Aug 2019 at 06:15, Malik Yousef <malik.yousef at gmail.com> wrote:
>
>> Hello
>> When in using the scoring to be 'f1' then i get an error.
>> Here is the code and the error
>>
>> X=data
>> y=target_column
>> classifier = LinearSVC()
>> rfecv = RFECV(estimator=classifier, step=0.1,
>> cv=StratifiedKFold(5),scoring='f1')
>> rfecv.fit(X, y)
>>
>> The error is :
>> ValueError: pos_label=1 is not a valid label: array([u'c.pre', u'n.pre'],
>> dtype='<U5')
>>
>> Please your help
>> (I'm new to using scikit-leanr)
>>
>> ---------------------------------------------------------------------------------------
>> *Prof. Malik Yousef , Associate Professor                           *
>> *Zefat Academic College , Department of Information System  *
>> Home Page:
>> https://malikyousef.com/
>> Google Scholar Profile :
>> https://scholar.google.com/citations?user=9UCZ_q4AAAAJ&hl=en&oi=ao
>>
>> ----------------------------------------------------------------------------------------------------
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