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> 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@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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