Shap

This release is just to refresh the Windows builds on AppVeyor that didn't complete for 0.28.4

- Fixes memory corruption error from TreeExplainer (courtesy of imatiach-msft)
- Adds support for skopt Random Forest and ExtraTrees Regressors (courtesy of Bacoknight)
- Adds support for matplotlib forceplot with text rotation (courtesy of vatsan)
- Adds a save_html function

- Fix some plot coloring issues introduced by 0.28 (such as 406)

- Downgrade numpy API usage to support older versions.

- Fixes a byte-alignment issue on Windows when loading XGBoost models.
- Now matches tree_limit use in XGBoost models courtesy of HughChen
- Fix an issue with the expected_value of transformed model outputs in TreeExplainer

- Add support for rank-based feature selection in `KernelExplainer`.
- Depreciate `l1_reg="auto"` in `KernelExplainer` in favor of eventually defaulting to `l1_reg="num_features(10)"`
- New color scales based on the Lch color space.
- Better auto-color choices for multi-class summary plots.
- Better plotting of NaN values in dependence_plots
- Updates for Pytorch 1.0 courtesy of gabrieltseng
- Fix the sklearn DecisionTreeClassifier handling to correctly normalize to a probability output
- Enable multi-output model support for `TreeExplainer` when `feature_dependence="independent"`
- Correctly load the objective of LightGBM models for use in explaining the model loss.
- Fix numerical precision mismatch with sklearn models.
- Fix numerical precision mismatch with XGBoost models by now directly loading from memory instead of JSON.