Re: [scikit-learn] SVM-RFE

It does not provide access for tracing the step by step feature weights and predictive ability- The user provides the n_feature. Malik --- *Prof. Malik Yousef (Associate Professor) * *The Head of the** Galilee

[scikit-learn] SVM-RFE

, 800 features,,2 features, 1 feature. Also, I want to keep track of the features in each level. [image: image.png] Best --- *Prof. Malik Yousef (Associate Professor) * *The Head of the** Galilee Digital H

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

. 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_q4J&hl=en&a

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

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

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_q4AA

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

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 la