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Implement GLM estimators in dask-ml #94

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merged 14 commits into from Dec 1, 2017

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TomAugspurger commented Nov 15, 2017

Moving them here from dask-glm.

No changes to the API yet.

Implement GLM estimators in dask-ml
Moving them here from dask-glm
@PeterDSteinberg

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PeterDSteinberg commented Nov 15, 2017

Thanks @TomAugspurger - you beat me to it - Is the goal for this PR to make dask-glm installation no longer required for dask-ml - essentially moving all of its assets to the new subpackage here? That would be my vote but it's not critical to me.

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TomAugspurger commented Nov 15, 2017

dask-glm will still be a required dependency, as the optimizers and regularizers will still live there. Just the scikit-learn style estimators are moving here.

@@ -82,6 +82,48 @@ def make_counts(n_samples=1000, n_features=100, n_informative=2, scale=1.0,
return X, y
def make_poisson(n_samples=1000, n_features=100, n_informative=2, scale=1.0,

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MLnick Nov 22, 2017

This seems to be exactly the same as make_counts above? Is it meant to be a copy-over of the make_classification and make_regression from GLM?

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TomAugspurger Nov 26, 2017

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Whoops, thanks.

@TomAugspurger TomAugspurger merged commit 0667ea3 into dask:master Dec 1, 2017

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@TomAugspurger TomAugspurger deleted the TomAugspurger:glm-estimators branch Dec 1, 2017

TomAugspurger added a commit to daniel-severo/dask-ml that referenced this pull request Jan 15, 2018

Implement GLM estimators in dask-ml (dask#94)
* Implement GLM estimators in dask-ml

Moving them here from dask-glm

* Flake8 fixups

* Added multipledispatch

* Refactor

Match scikit-learn style, handle dataframe

* More API changes

* More solver kwarg validation

* Cleanup imports

* Docstring

* Added release notes

* Reformat

* Encoding

* Remove duplicate poisson
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