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

[Guillaume Lemaître]

You can look a the string example: https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html Sent from my phone - sorry to be brief and potential misspell. From: malik.you...@gmail.com Sent: 1 August 2019 23:19 To: scikit-learn@python.org Reply to: scikit-learn@python.org Subject: Re: [scikit-learn] SVM-RFE with scoring = 'f1' Can you give me an example? --------------------------------------------------------------------------------------- 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 ---------------------------------------------------------------------------------------------------- On Thu, Aug 1, 2019 at 5:15 PM Guillaume Lemaître <g.lemaitr...@gmail.com> wrote: you can use the LabelEncoder then. It will encode the classes for you. On Thu, 1 Aug 2019 at 23:04, Malik Yousef <malik.you...@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. --------------------------------------------------------------------------------------- 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 ---------------------------------------------------------------------------------------------------- On Thu, Aug 1, 2019 at 4:58 PM Guillaume Lemaître <g.lemaitr...@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.you...@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 ---------------------------------------------------------------------------------------------------- _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn -- Guillaume Lemaitre INRIA Saclay - Parietal team Center for Data Science Paris-Saclay https://glemaitre.github.io/ _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn -- Guillaume Lemaitre INRIA Saclay - Parietal team Center for Data Science Paris-Saclay https://glemaitre.github.io/ _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

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