Yellowbrick v0.8

Yellowbrick is an open source, pure Python project that extends the scikit-learn API with visual analysis and diagnostic tools. The Yellowbrick API also wraps matplotlib to create publication-ready figures and interactive data explorations while still allowing developers fine-grain control of figures. For users, Yellowbrick can help evaluate the performance, stability, and predictive value of machine learning models and assist in diagnosing problems throughout the machine learning workflow.

Major Changes 

• Added support metric to ClassificationReport visualizer 
• Created a gallery of visualizations in Yellowbrick 
• Improved the performance of ParallelCoordinates with fast and slow drawing algorithms
• ResidualsPlot now has a histogram of error density 
• Adds biplot to PCADecomposition visualization 
• Added alpha transparency to RadViz visualizer 
• Adds DispersionPlot for text analysis 
• Created a prototype of the CVScores visualizer (undocumented)
• Bug fix for usage of multidimensional arrays in FeatureImportance visualizer 
• Adds datasaurus dataset to show importance of visualizing data 

Minor Changes:

• Add options for support parameter to ClassificationReport 
• Add fast and alpha options to ParallelCoordinates
• Fix grammar in tutorial.rst 
• Added note to tutorial indicating subtle differences when working in Jupyter notebooks 
• Updated issue and pull request templates 
• Added test to check for NLTK postag data availability 
• Clarify quick start documentation 
• Deprecated the ScatterVisualizer 
• Deprecated the DecisionBoundary visualizer 
• Deprecated ThresholdVisualization aliases