Sounds good.. tried it and works.. thank you! On Mon, Aug 28, 2017 at 3:20 PM, Andreas Mueller <t3k...@gmail.com> wrote:
> you can also use grid.best_estimator_ (and then all the rest) > > On 08/28/2017 03:07 PM, Raga Markely wrote: > > 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 >> >> > > > _______________________________________________ > 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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