Hi everyone,
As Joel and Andreas suggested (see thread), I've created a new pull request
which enables sample weights in logistic regression for 2 of the 3 solvers
(lbfgs and newton-cg). See:
https://github.com/scikit-learn/scikit-learn/pull/5204
Thanks,
Valentin
On Sat, Aug 29, 2015 at 4:27 AM, Joel Nothman <[email protected]>
wrote:
> new and small PR is best.
>
> On 29 August 2015 at 03:35, Valentin Stolbunov <
> [email protected]> wrote:
>
>> Sounds good. Does anyone happen to know of any PRs that are related and
>> close to being accepted? Or do you think a new PR is the best option in
>> this case?
>>
>> On Thu, Aug 27, 2015 at 6:33 PM, Joel Nothman <[email protected]>
>> wrote:
>>
>>> +1
>>>
>>> On 28 August 2015 at 04:23, Andreas Mueller <[email protected]> wrote:
>>>
>>>> I think it would be fine to enable it now without support in all
>>>> solvers.
>>>>
>>>>
>>>> On 8/27/2015 11:29 AM, Valentin Stolbunov wrote:
>>>>
>>>> Joel, I see you've done some work in that PR. Is an additional review
>>>> all that's needed there? Looks like changes in Logistic Regression CV broke
>>>> the original contribution and it has since stalled (over 1 year ago).
>>>>
>>>> I guess the big question is: what is the best way to get sample weights
>>>> in LR? Would it be to wait for progress in that PR and have weights for all
>>>> solvers, or simply "enable" them in the other two solvers via the rough
>>>> steps I outlined earlier?
>>>>
>>>> On Wed, Aug 26, 2015 at 9:59 PM, Andy <[email protected]> wrote:
>>>>
>>>>> On 08/26/2015 09:29 PM, Joel Nothman wrote:
>>>>> > I agree. I suspect this was an unintentional omission, in fact.
>>>>> >
>>>>> > Apart from which, sample_weight support in liblinear could be merged
>>>>> > from https://github.com/scikit-learn/scikit-learn/pull/2784 which is
>>>>> > dormant, and merely needs some core contributors to show interest in
>>>>> > merging it...
>>>>> >
>>>>> "merely" ;)
>>>>>
>>>>>
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