Version 0.6
Markdown for GitHub repo:
Deployed: Saturday, March 17, 2018
Contributors: @bbengfort, @ndanielsen, @rebeccabilbro, @lwgray, @Kautumn06, @georgerichardson, @pbs929, @Aylr, @gary-mayfield, @jkeung
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 offeature_importances_
orcoef_
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
, andRank2D
. - 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 ofnp.tolist
to avoid NumPy deprecation warning. DataVisualizer
updated to removenp.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 0.7DecisionBoundaryVisualizer
is being moved to contrib in 0.7