Open TomAugspurger opened 6 years ago
Right now we only have support for about 7 metrics in https://github.com/dask/dask-ml/blob/master/dask_ml/metrics/__init__.py
Not all of these will be easily doable.
Can you expand upon this?
Can you expand upon this?
Just a suspicion that I haven't verified. e.g. https://github.com/scikit-learn/scikit-learn/blob/a24c8b46/sklearn/metrics/ranking.py#L39 is doing some things with ordering (maybe just checks) that looks hard to do in parallel.
@TomAugspurger I want to work on this. Any inputs?
Thanks.
I think a valuable mini-project would be to see how many of scikit-learn's metrics will work properly on dask arrays with NEP-18: https://www.numpy.org/neps/nep-0018-array-function-protocol.html. I think that dask master implements the protocol now.
If possible, I would prefer to deprecate dask-ml's metrics, and get various projects (dask-ml, cuML) using the same implementation (scikit-learn's presumably).
On Wed, Apr 10, 2019 at 6:20 PM Sriharsha Atyam notifications@github.com wrote:
@TomAugspurger https://github.com/TomAugspurger I want to work on this. Any inputs?
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https://mail.python.org/pipermail/scikit-learn/2019-May/003118.html asks about incremental cluster scoring.
more generally, https://scikit-learn.org/stable/modules/classes.html#clustering-metrics
I think a valuable mini-project would be to see how many of scikit-learn's metrics will work properly on dask arrays with NEP-18: https://www.numpy.org/neps/nep-0018-array-function-protocol.html.
To clarify: I don't think this should preclude implementing the metrics here in dask-ml first. Getting metrics to work well with a variety of arrays is a big project that will take a while.
Tags: @TomAugspurger @stsievert Hello, can I work on the issue titled "Expand our metrics #213".
We have the basics, without weights.
http://scikit-learn.org/stable/modules/classes.html#sklearn-metrics-metrics
Not all of these will be easily doable.