Extends the existing sequence classification explainer into a new explainer that independently produces attributions for each label in the model regardless of what the predicted class is. This allows users to better inspect and interpret model predictions across all classes, particularly in situations where classifiers might be used in a multilabel fashion.
The MultiLabelClassificationExplainer returns a dictionary mapping labels/classes to a list of word attributions, additionally the visualize() method will display the entire table of attributions for each label.
This has been a very requested feature for a number of months so we're very happy to get it released (finally)
PR Description
Extends the existing sequence classification explainer into a new explainer that independently produces attributions for each label in the model regardless of what the predicted class is. This allows users to better inspect and interpret model predictions across all classes, particularly in situations where classifiers might be used in a multilabel fashion.
The
MultiLabelClassificationExplainerreturns a dictionary mapping labels/classes to a list of word attributions, additionally thevisualize()method will display the entire table of attributions for each label.This has been a very requested feature for a number of months so we're very happy to get it released (finally)
CC: @MichalMalyska @rhettdsouza13 @fraserprice @JensVN98 @dheerajiiitv
Motivation and Context
References issue: #39
Tests and Coverage
Types of changes
Final Checklist: