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

[Raga Markely]

No worries.. ur answer is helpful for me too.. I was actually exploring
different ways to get the coeff, what i can and can't get :)..

Thanks!

On Aug 28, 2017 8:24 PM, "Joel Nothman" <joel.nothman at gmail.com> wrote:

> Sorry if I misunderstood your question.
>
> On 29 August 2017 at 06:32, Raga Markely <raga.markely at gmail.com> wrote:
>
>> Sounds good.. tried it and works.. thank you!
>>
>> On Mon, Aug 28, 2017 at 3:20 PM, Andreas Mueller <t3kcit at 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 <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>
>>>> 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
>>>>> > 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>
>>>>>> 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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>>>>>>
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