[scikit-learn] Calculate p-value, the measure of statistical significance, in scikit-learn

[Andrew Howe]

Yep - in which case the OP would have difficulty computing p-values (but
not the other usual stats) with any software tool that provided those
methods.  But since the question was specifically about scikit-learn, my
main point is that the quantities are easy to compute (if they exist).

Andrew

<~~~~~~~~~~~~~~~~~~~~~~~~~~~>
J. Andrew Howe, PhD
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On Sat, Feb 4, 2017 at 10:52 PM, Nelle Varoquaux <nelle.varoquaux at gmail.com>
wrote:

>
> I'm fairly certain that the scikit-learn regression result, plus what you
>> already have about the data is enough for you to compute all those
>> statistical measures yourself.  It should be rather trivial to do so.
>>
>
> That is highly dependent on the regression model you use. For example
> computing a p-value for a lasso regression parameter is not so trivial,
> though a significance test has recently been proposed.
>
>
>>
>> Andrew
>>
>> On Feb 4, 2017 00:34, "Afarin Famili" <Afarin.Famili at utsouthwestern.edu>
>> wrote:
>>
>>> Hi all,
>>>
>>> I am aiming at calculating the p-value of regression models using
>>> scikit-learn, in order to report their statistical significance. Aside from
>>> permutation_test_score in scikit-learn, do you have any suggestions for
>>> calculating the p-value of the model? Ultimately, I am interested in
>>> computing the coefficient of determination, r2 as well as MSE to indicate
>>> the performance of the model for those models that were statistically
>>> significant.
>>>
>>> Thank you,
>>>
>>> Afarin​
>>>
>>> ​
>>>
>>>
>>>
>>> ------------------------------
>>>
>>> UT Southwestern
>>>
>>> Medical Center
>>>
>>> The future of medicine, today.
>>>
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>
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