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, RagaOn Mon, Aug 28, 2017 at 12:01 PM, Andreas Mueller <[email protected] <mailto:[email protected]>> 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 <[email protected] <mailto:[email protected]>> 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 <[email protected] <mailto:[email protected]>> 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 [email protected] <mailto:[email protected]> https://mail.python.org/mailman/listinfo/scikit-learn <https://mail.python.org/mailman/listinfo/scikit-learn> _______________________________________________ scikit-learn mailing list [email protected] <mailto:[email protected]> https://mail.python.org/mailman/listinfo/scikit-learn <https://mail.python.org/mailman/listinfo/scikit-learn> _______________________________________________ scikit-learn mailing list [email protected] <mailto:[email protected]> https://mail.python.org/mailman/listinfo/scikit-learn <https://mail.python.org/mailman/listinfo/scikit-learn>_______________________________________________ scikit-learn mailing list [email protected] <mailto:[email protected]> https://mail.python.org/mailman/listinfo/scikit-learn <https://mail.python.org/mailman/listinfo/scikit-learn> _______________________________________________ scikit-learn mailing list [email protected] https://mail.python.org/mailman/listinfo/scikit-learn
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