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

[Guillaume Lemaître]

you can use the LabelEncoder then. It will encode the classes for you.

On Thu, 1 Aug 2019 at 23:04, Malik Yousef <malik.yousef at gmail.com> wrote:

> The only string column is the label column(class labels, n.pre, and
> c.pre). if the scoring = 'accuracy' then it works fine.
> So I think I need somehow to set up the postive_lable.. that I don't know
> how to do that.
>
>
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> *Prof. Malik Yousef , Associate Professor                           *
> *Zefat Academic College , Department of Information System  *
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>
> On Thu, Aug 1, 2019 at 4:58 PM Guillaume Lemaître <g.lemaitre58 at gmail.com>
> wrote:
>
>> It looks like your data contains string. You need to make some
>> preprocessing before to give it the linear model.
>>
>> On Thu, 1 Aug 2019 at 22:16, 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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>>
>>
>> --
>> Guillaume Lemaitre
>> INRIA Saclay - Parietal team
>> Center for Data Science Paris-Saclay
>> https://glemaitre.github.io/
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-- 
Guillaume Lemaitre
INRIA Saclay - Parietal team
Center for Data Science Paris-Saclay
https://glemaitre.github.io/
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