Ah.. got it :D.. The pipeline was run in gridsearchcv..
It works now after calling fit.. Thanks! Raga On Mon, Aug 28, 2017 at 2:55 PM, Andreas Mueller <t3k...@gmail.com> wrote: > Have you called "fit" on the pipeline? > > > On 08/28/2017 02:12 PM, Raga Markely wrote: > > Thank you, Andreas. > > When I try > >> pipe_lr.named_steps['clf'].coef_ > > > I get: > >> AttributeError: 'LogisticRegression' object has no attribute 'coef_' > > > And when I try: > >> pipe_lr.named_steps['clf'] > > > I get: > >> LogisticRegression(C=0.1, class_weight=None, dual=False, >> fit_intercept=True, intercept_scaling=1, max_iter=100, multi_class='ovr', >> n_jobs=1, penalty='l2', random_state=None, solver='liblinear', tol=0.0001, >> verbose=0, warm_start=False) > > > I wonder what I am missing? > > Thanks, > Raga > > > On Mon, Aug 28, 2017 at 12:01 PM, Andreas Mueller <t3k...@gmail.com> > wrote: > >> Can can get the coefficients on the scaled data with >> pipeline_lr.named_steps_['clf'].coef_ >> though >> >> >> On 08/28/2017 12:08 AM, Raga Markely wrote: >> >> No problem, thank you! >> >> Best, >> Raga >> >> On Mon, Aug 28, 2017 at 12:01 AM, Joel Nothman <joel.noth...@gmail.com> >> wrote: >> >>> No, we do not have a way to get the coefficients with respect to the >>> input (pre-scaling) space. >>> >>> On 28 August 2017 at 13:20, Raga Markely <raga.mark...@gmail.com> wrote: >>> >>>> Hello, >>>> >>>> I am wondering if it's possible to get the weight coefficients of >>>> logistic regression from a pipeline? >>>> >>>> For instance, I have the followings: >>>> >>>>> clf_lr = LogisticRegression(penalty='l1', C=0.1) >>>>> pipe_lr = Pipeline([['sc', StandardScaler()], ['clf', clf_lr]]) >>>>> pipe_lr.fit(X, y) >>>> >>>> >>>> Does pipe_lr have an attribute that I can call to get the weight >>>> coefficient? >>>> >>>> Or do I have to get it from the classifier as follows? >>>> >>>>> X_std = StandardScaler().fit_transform(X) >>>>> clf_lr = LogisticRegression(penalty='l1', C=0.1) >>>>> clf_lr.fit(X_std, y) >>>>> clf_lr.coef_ >>>> >>>> >>>> Thank you, >>>> Raga >>>> >>>> >>>> _______________________________________________ >>>> 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 >>> >>> >> >> >> _______________________________________________ >> scikit-learn mailing >> listscikit-learn@python.orghttps://mail.python.org/mailman/listinfo/scikit-learn >> >> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > > _______________________________________________ > scikit-learn mailing > listscikit-learn@python.orghttps://mail.python.org/mailman/listinfo/scikit-learn > > > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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