Temporal Rule-Based Counterfactual Explanations for Multivariate Time Series-Reference-Cited by-同舟云学术

Temporal Rule-Based Counterfactual Explanations for Multivariate Time Series

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)
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Author:

Bahri Omar¹,Li Peiyu¹,Boubrahimi Soukaina Filali¹,Hamdi Shah Muhammad¹

Affiliation:

1. Utah State University,Department of Computer Science,Logan,UT,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10068862/10068777/10069254.pdf?arnumber=10069254

Reference31 articles.

1. Explaining machine learning classifiers through diverse counterfactual explanations

2. Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives;dhurandhar;Advances in neural information processing systems,2018

3. Time series shapelets: a novel technique that allows accurate, interpretable and fast classification

4. Counterfactual Explanations for Multivariate Time Series

5. The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances

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