This version primarily repairs the dependency issues we faced with scipy 1.6, scikit-learn 0.24 and Python 3.6 (or earlier). As part of the rapidly changing Python library landscape, we've been forced to react quickly to dependency changes, even where those libraries have been responsibly issuing future and deprecation warnings in our code base.
- Implement new
get_paramson ModelVisualizers to ensure wrapped estimator is being correctly accessed via the new Estimator methods.
- Fix the test dependencies to prevent variability in CI (must periodically review dependencies to ensure we're testing what our users are experiencing).
estimatorparam to ensure that Visualizer arguments match their property names so that inspect works with get and set params and other scikit-learn utility functions.
- Import scikit-learn private API
- Remove any calls to
- Modify test fixtures and baseline images to accommodate new sklearn implementation
- Set the numpy dependency to be less than 1.20 because this is causing Pickle issues with joblib and umap
shuffle=Trueargument to any CV class that uses a random seed.
- Set our CI matrix to Python and Miniconda 3.7 and 3.8