Update shap to 0.35.0

[pyup-bot]

This PR updates shap from 0.30.2 to 0.35.0.

Changelog

0.35.0

This release includes:

- Better support for TensorFlow 2 (thanks imatiach-msft)
- Support for NGBoost models in TreeExplainer (thanks zhiruiwang)
- TreeExplainer support for the new sklearn.ensemble.HistGradientBoosting model.
- New improved versions of PartitionExplainer for images and text.
- IBM zOS compatibility courtesy of DorianCzichotzki.
- Support for XGBoost 1.0
- Many bug fixes courtesy of Ivan, Christian Paul, RandallJEllis, and ibuda.

0.34.0

This release includes:
- Many small bug fixes.
- Better matplotlib text alignment during rotation courtesy of koomie
- Cleaned up the C++ transformer code to allow easier PRs.
- Fixed a too tight check_additivity tolerance in TreeExplainer 950
- Updated the LinearExplainer API to match TreeExplainer
- Allow custom class ordering in a summary_plot courtesy of SimonStreicher

0.33.0

This release contains various bug fixes and new features including:

- Added PySpark support for TreeExplainer courtesy of QuentinAmbard
- A new type of plot that is an alternative to the force_plot, a `waterfall_plot`
- A new PermutationExplainer that is an alternative to KernelExplainer and SamplingExplainer.
- Added `return_variances` to GradientExplainer for PyTorch courtesy of s6juncheng 
- Now we use exceptions rather than assertions in TreeExplainer courtesy of ssaamm
- Fixed image_plot transpose issue courtesy of Jimbotsai
- Fix color bar axis attachment issue courtesy of Lasse Valentini Jensen
- Fix tensor attachment issue in PyTorch courtesy of gabrieltseng 
- Fix color clipping ranges in summary_pot courtesy of joelostblom
- Address sklearn 0.22 API changes courtesy of lemon-yellow
- Ensure matplotlib is optional courtesy of imatiach-msft

0.32.1

This release is just intended to push better auto-deploy bundles out of travis and appveyor.

0.32.0

This release includes:
- Support for sklearn isolation forest courtesy of JiechengZhao 
- New check_additivity tests to ensure no errors in DeepExplainer and TreeExplainer
- Fix 861, 860 
- Fix missing readme example html file
- Support for spark decision tree regressor courtesy of QuentinAmbard 
- Better safe isinstance checking courtesy of parsatorb
- Fix eager execution in TF < 2 courtesy of bottydim

0.31.0

This release contains several new features and bug fixes:
- GradientExplainer now supports TensorFlow 2.0.
- We now do a lazy load of the plotting dependencies, which means a pip install no longer needs to also pull in matplotlib, skimage, and ipython. This should make installs much lighter, especially those that don't need plotting :)
- Added a new BruteForceExplainer for easy testing and comparison on small problems.
- Added a new partial_dependence_plot function. This function will be used to illustrate the close connections between partial dependence plots and SHAP values in future example notebooks.
- Handle the multiclass case with no intercept in LinearExplainer courtesy of gabrieltseng 
- Some extras_require options during the pip install courtesy of AbdealiJK 
- Other small bug fixes and updates

Links

• PyPI: https://pypi.org/project/shap
• Changelog: https://pyup.io/changelogs/shap/
• Repo: http://github.com/slundberg/shap