Yellowbrick v0.6

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.

Changes 

• New Feature! The FeatureImportances Visualizer enables the user to visualize the most informative (relative and absolute) features in their model, plotting a bar graph of feature_importances_ or coef_ attributes.
• New Feature! The ExplainedVariance Visualizer produces a plot of the explained variance resulting from a dimensionality reduction to help identify the best tradeoff between number of dimensions and amount of information retained from the data.
• New Feature! The GridSearchVisualizer creates a color plot showing the best grid search scores across two parameters.
• New Feature! The ClassPredictionError Visualizer is a heatmap implementation of the class balance visualizer, which provides a way to quickly understand how successfully your classifier is predicting the correct classes.
• New Feature! The ThresholdVisualizer allows the user to visualize the bounds of precision, recall and queue rate at different thresholds for binary targets after a given number of trials.
• New MultiFeatureVisualizer helper class to provide base functionality for getting the names of features for use in plot annotation.
• Adds font size param to the confusion matrix to adjust its visibility.
• Add quick method to the confusion matrix
• Tests: In this version, we've switched from using nose to pytest. Image comparison tests have been added and the visual tests are updated to matplotlib 2.2.0. Test coverage has also been improved for a number of visualizers, including JointPlot, AlphaPlot, FreqDist, RadViz, ElbowPlot, SilhouettePlot, ConfusionMatrix, Rank1D, and Rank2D.
• Documentation updates, including discussion of Image Comparison Tests for contributors.

Bug Fixes:

• Fixes the resolve_colors function. You can now pass in a number of colors and a colormap and get back the correct number of colors.
• Fixes TSNEVisualizer Value Error when no classes are specified.
• Adds the circle back to RadViz! This visualizer has also been updated to ensure there's a visualization even when there are missing values
• Updated RocAuc to correctly check the number of classes
• Switch from converting structured arrays to ndarrays using np.copy instead of np.tolist to avoid NumPy deprecation warning.
• DataVisualizer updated to remove np.nan values and warn the user that nans are not plotted.
• ClassificationReport no longer has lines that run through the numbers, is more grid-like

Deprecation Warnings:

• ScatterPlotVisualizer is being moved to contrib in 0.7
• DecisionBoundaryVisualizer is being moved to contrib in 0.7