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Hardened the Yellowbrick API to elevate the idea of a Visualizer to a first principle. This included reconciling shifts in the development of the preliminary versions to the new API, formalizing Visualizer methods like
finalize(), and adding utilities that revolve around Scikit-Learn. To that end we also performed administrative tasks like refreshing the documentation and preparing the repository for more and varied open source contributions.
- Converted Mkdocs documentation to Sphinx documentation
- Updated docstrings for all Visualizers and functions
- Created a DataVisualizer base class for dataset visualization
- Single call functions for simple visualizer interaction
- Added yellowbrick specific color sequences and palettes and env handling
- More robust examples with downloader from DDL host
- Better axes handling in visualizer, matplotlib/sklearn integration
- Added a finalize method to complete drawing before render
- Improved testing on real data sets from examples
- Score visualizer renders in notebook but not in Python scripts.
- Tests updated to support new API