Review: Explainable AutoML�Balancing Automation and Transparency

review
Received: Dec 13, 2023
Published: Dec 31, 2023
Authors: Hiroa Vasquez ✉ Suri Dumont

Abstract

We analyze recent trends in explainable AutoML pipelines focusing on interpretability frameworks and bias quantification methods.

⬇ Download

Cite this article

Vasquez, H. & Dumont, S. (2023). Review: Explainable AutoML�Balancing Automation and Transparency. Research Explorations in Global Knowledge & Technology (REGKT), 2 (10). Retrieved from https://regkt.com/article.php?id=497&slug=review-explainable-automl-balancing-automation-transparency

Premium Membership Required

You need a premium account to view or download this article.

Become Premium