-
-
Notifications
You must be signed in to change notification settings - Fork 256
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Implement GLM estimators in dask-ml #94
Conversation
Moving them here from dask-glm
Thanks @TomAugspurger - you beat me to it - Is the goal for this PR to make |
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. |
dask_ml/datasets.py
Outdated
@@ -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, |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
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?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Whoops, thanks.
* 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
Moving them here from dask-glm.
No changes to the API yet.