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 > >
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