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@bbengfort bbengfort released this 09 Oct 19:34
· 67 commits to develop since this release

Deployed: Friday, October 9, 2020
Current Contributors: @rebeccabilbro, @lwgray, @VladSkripniuk, @Express50, @pdamodaran, @aldermartinez, @tktran, @bbengfort, @melonhead901, @Kautumn06, @ojedatony1616, @eschmier, @wagner2010, @ndanielsen

Major Changes:

  • Added Q-Q plot as side-by-side option to the ResidualsPlot visualizer.
  • More robust handling of binary classification in ROCAUC visualization, standardizing the way that classifiers with predict_proba and decision_function methods are handling. A binary hyperparameter was added to the visualizer to ensure correct interpretation of binary ROCAUC plots.
  • Fixes to ManualAlphaSelection to move it from prototype to prime time including documentation, tests, and quick method. This method allows users to perform alpha selection visualization on non-CV estimators.
  • Removal of AppVeyor from the CI matrix after too many out-of-core (non-Yellowbrick) failures with setup and installation on the VisualStudio images. Yellowbrick CI currently omits Windows and Miniconda from the test matrix and we are actively looking for new solutions.
  • Third party estimator wrapper in contrib to provide enhanced support for non-scikit-learn estimators such as those in Keras, CatBoost, and cuML.

Minor Changes:

  • Allow users to specify colors for the PrecisionRecallCurve.
  • Update ClassificationScoreVisualizer base class to have a class_colors_ learned attribute instead of a colors property; additional polishing of multi-class colors in PrecisionRecallCurve, ROCAUC, and ClassPredictionError.
  • Update KElbowVisualizer fit method and quick method to allow passing sample_weight parameter through the visualizer.
  • Enhancements to classification documentation to better discuss precision and recall and to diagnose with PrecisionRecallCurve and ClassificationReport visualizers.
  • Improvements to CooksDistance visualizer documentation.
  • Corrected KElbowVisualizer label and legend formatting.
  • Typo fixes to ROCAUC documentation, labels, and legend. Typo fix to Manifold documentation.
  • Use of tight_layout accessing the Visualizer figure property to finalize images and resolve discrepancies in plot directive images in documentation.
  • Add get_param_names helper function to identify keyword-only parameters that belong to a specific method.
  • Splits package namespace for yellowbrick.regressor.residuals to move PredictionError to its own module, yellowbrick.regressor.prediction_error.
  • Update tests to use SVC instead of LinearSVC and correct KMeans scores based on updates to scikit-learn v0.23.
  • Continued maintenance and management of baseline images following dependency updates; removal of mpl.cbook dependency.
  • Explicitly include license file in source distribution via MANIFEST.in.
  • Fixes to some deprecation warnings from sklearn.metrics.
  • Testing requirements depends on Pandas v1.0.4 or later.
  • Reintegrates pytest-spec and verbose test logging, updates pytest dependency to v0.5.0 or later.
  • Added Pandas v0.20 or later to documentation dependencies.