Maximum Entropy Baseline for Integrated Gradients

04/12/2022
by   Hanxiao Tan, et al.
0

Integrated Gradients (IG), one of the most popular explainability methods available, still remains ambiguous in the selection of baseline, which may seriously impair the credibility of the explanations. This study proposes a new uniform baseline, i.e., the Maximum Entropy Baseline, which is consistent with the "uninformative" property of baselines defined in IG. In addition, we propose an improved ablating evaluation approach incorporating the new baseline, where the information conservativeness is maintained. We explain the linear transformation invariance of IG baselines from an information perspective. Finally, we assess the reliability of the explanations generated by different explainability methods and different IG baselines through extensive evaluation experiments.

READ FULL TEXT

page 4

page 5

page 6

page 7

page 9

page 11

page 15

research
07/21/2020

Pattern-Guided Integrated Gradients

Integrated Gradients (IG) and PatternAttribution (PA) are two establishe...
research
02/23/2023

The Generalizability of Explanations

Due to the absence of ground truth, objective evaluation of explainabili...
research
08/12/2022

Comparing Baseline Shapley and Integrated Gradients for Local Explanation: Some Additional Insights

There are many different methods in the literature for local explanation...
research
11/12/2021

Generalized active information: extensions to unbounded domains

In the last three decades, several measures of complexity have been prop...
research
04/28/2020

Towards Prediction Explainability through Sparse Communication

Explainability is a topic of growing importance in NLP. In this work, we...
research
06/08/2020

A Baseline for Shapely Values in MLPs: from Missingness to Neutrality

Being able to explain a prediction as well as having a model that perfor...
research
03/21/2023

Explain To Me: Salience-Based Explainability for Synthetic Face Detection Models

The performance of convolutional neural networks has continued to improv...

Please sign up or login with your details

Forgot password? Click here to reset