[scikit-learn] Sprint discussion points?
Nicolas Hug
niourf at gmail.com
Thu Feb 14 11:40:05 EST 2019
> or we could go as far as to schedule meetings on the different topics.
Given the number of issues to discuss this is probably the best approach IMO
On 2/14/19 8:31 AM, Andreas Mueller wrote:
>
> As I said, I think it's too much and we need to prioritize.
>
> We could either rank issues and start with some and see how far we
> get, or we could go as far as to schedule meetings on the different
> topics.
>
> Also, I'll be only arriving Tuesday late morning, I think.
>
>
> On 2/14/19 8:05 AM, Adrin wrote:
>> I've been working on some bias mitigation metrics and methods and
>> that usecase
>> changes the data as well as up/down sampling as a transformer. Almost
>> all those
>> methods also need sample properties for the observations to work. I'm
>> trying to
>> make them "sklearn compatible", but for now it's pretty hacky. So I'd
>> be happy if
>> we discuss the union of what Joel and Andy suggest.
>>
>> Cheers,
>> Adrin.
>>
>> On Thu, Feb 14, 2019, 11:47 Guillaume Lemaître
>> <g.lemaitre58 at gmail.com <mailto:g.lemaitre58 at gmail.com> wrote:
>>
>> I am really interested in the union of the list given by Andy and
>> Joel.
>>
>> I'll like to have some discussions related to the "impute"
>> module. Compare to the other topics, it is not a high priority
>> discussion thought.
>>
>> On Thu, 14 Feb 2019 at 05:31, Joel Nothman
>> <joel.nothman at gmail.com <mailto:joel.nothman at gmail.com>> wrote:
>>
>> Convergence in logistic regression
>> (https://github.com/scikit-learn/scikit-learn/issues/11536) is
>> indeed one problem (and it presents a general issue of what
>> max_iter means when you have several solvers, or how good
>> defaults are selected). But I was sure we had problems with
>> non-determinism on some platforms... but now can't find.
>>
>> > my students have basically no way to figure out what
>> features the coefficients in their linear model correspond
>> to, that seems a bit more important to me.
>>
>> Yes, I agree... Assuming coefficients are helpful, rather
>> than using permutation-based measures of importance, for
>> instance.
>>
>> I generally think a review of distances might be a good thing
>> at some point, given the confusing triplication across
>> sklearn.neighbors, sklearn.metrics.pairwise, scipy.spatial...
>> and that minkowski,p=2 is not implemented the same as euclidean.
>>
>>
>> On Thu, 14 Feb 2019 at 12:56, Andreas Mueller
>> <t3kcit at gmail.com <mailto:t3kcit at gmail.com>> wrote:
>>
>> Do you have a reference for the logistic regression
>> stability? Is it convergence warnings?
>>
>> Happy to discuss the other two issues, though I feel they
>> seem easier than most of what's on my list.
>>
>> I have no idea what's going on with OPTICS tbh, and I'll
>> leave it up to you and the others to decide whether
>> that's something we should discuss.
>> I can try to read up and weigh in but that might not be
>> the most effective way to do it.
>>
>> the sample props is something I left out because I
>> personally don't feel it's a priority compared to all the
>> other things;
>> my students have basically no way to figure out what
>> features the coefficients in their linear model
>> correspond to, that seems a bit more important to me.
>>
>> We can put it on the discussion list again, but I'm not
>> super enthusiastic about it.
>>
>> How should we prioritize things?
>>
>>
>> On 2/13/19 8:08 PM, Joel Nothman wrote:
>>> Yes, I was thinking the same. I think there are some
>>> other core issues to solve, such as:
>>>
>>> * euclidean_distances numerical issues
>>> * commitment to ARM testing and debugging
>>> * logistic regression stability
>>>
>>> We should also nut out OPTICS issues or remove it from
>>> 0.21. I'm still keen on trying to work out sample props
>>> (supporting weighted scoring at least), but perhaps I'm
>>> being persuaded this will never be a top-priority
>>> requirement, and the solutions add much complexity.
>>>
>>> On Thu, 14 Feb 2019 at 07:39, Andreas Mueller
>>> <t3kcit at gmail.com <mailto:t3kcit at gmail.com>> wrote:
>>>
>>> Hey all.
>>>
>>> Should we collect some discussion points for the sprint?
>>>
>>> There's an unusual amount of core-devs present and I
>>> think we should seize the opportunity.
>>> Maybe we should create a page in the wiki or add it
>>> to the sprint page?
>>>
>>> Things that are high on my list of priorities are:
>>>
>>> * slicing pipelines
>>> * add get_feature_names to pipelines
>>> * freezing estimator
>>> * faster multi-metric scoring
>>> * fit_transform doing something other than
>>> fit.transform
>>> * imbalance-learn interface / subsampling in pipelines
>>> * Specifying search spaces and valid hyper
>>> parameters
>>> (https://github.com/scikit-learn/scikit-learn/issues/13031).
>>> * allowing EstimatorCV-style speed-up in GridSearches
>>> * storing pandas column names and using them as
>>> feature names
>>>
>>>
>>> Trying to discuss all of these might be too much,
>>> but maybe we can figure out a subset and make sure
>>> we have sleps to discuss?
>>> Most of these issues are on the roadmap, issue 13031
>>> is reladed to #18 but not directly on the roadmap.
>>>
>>> Thanks,
>>> Andy
>>> _______________________________________________
>>> scikit-learn mailing list
>>> scikit-learn at python.org <mailto:scikit-learn at python.org>
>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>
>>>
>>> _______________________________________________
>>> scikit-learn mailing list
>>> scikit-learn at python.org <mailto:scikit-learn at python.org>
>>> https://mail.python.org/mailman/listinfo/scikit-learn
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org <mailto:scikit-learn at python.org>
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org <mailto:scikit-learn at python.org>
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>>
>>
>> --
>> Guillaume Lemaitre
>> INRIA Saclay - Parietal team
>> Center for Data Science Paris-Saclay
>> https://glemaitre.github.io/
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org <mailto:scikit-learn at python.org>
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>>
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20190214/1f507706/attachment-0001.html>
More information about the scikit-learn
mailing list