[scikit-learn] Getting weight coefficient of logistic regression from a pipeline

[Andreas Mueller]

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 <t3kcit at gmail.com 
> <mailto:t3kcit at 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
>>     <t3kcit at gmail.com <mailto:t3kcit at 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.nothman at gmail.com <mailto:joel.nothman at 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.markely at gmail.com <mailto:raga.markely at 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
>>>
>>>
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