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 <t3k...@gmail.com
<mailto:t3k...@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
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