Implement GLM estimators in dask-ml #94
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Moving them here from dask-glm
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Thanks @TomAugspurger - you beat me to it - Is the goal for this PR to make |
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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. |
MLnick
reviewed
Nov 22, 2017
dask_ml/datasets.py
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| @@ -82,6 +82,48 @@ def make_counts(n_samples=1000, n_features=100, n_informative=2, scale=1.0, | |||
| return X, y | |||
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| def make_poisson(n_samples=1000, n_features=100, n_informative=2, scale=1.0, | |||
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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?
TomAugspurger
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to dsevero/dask-ml
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Jan 15, 2018
* 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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Moving them here from dask-glm.
No changes to the API yet.