User-Based Experiment Guidelines for Measuring Interpretability in Machine Learning

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférenceArticle dans les actes d'une conférence/un colloque

12 Téléchargements (Pure)

Résumé

With the advent of high-performance black-box models, interpretability is becoming a hot topic today in machine learning. While a lot of research is
done on interpretability, machine learning researchers do not have precise guidelines for setting up user-based experiments. This paper provides well-established guidelines from the human-computer interaction community.
langue originaleAnglais
titreEGC Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence
Lieu de publicationMetz, France
Etat de la publicationPublié - 2019

Empreinte digitale Examiner les sujets de recherche de « User-Based Experiment Guidelines for Measuring Interpretability in Machine Learning ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation