Generating contrastive explanations for inductive logic programming based on a near miss approach

In recent research, human-understandable explanations of machine learning models have received a lot of attention. Often explanations are given in form of model simplifications or visualizations. However, as shown in cognitive science as well as in early AI research, concept understanding can also b...

Full description

Saved in:

Bibliographic Details
Published in:	Machine learning Vol. 111; no. 5; pp. 1799 - 1820
Main Authors:	Rabold, Johannes, Siebers, Michael, Schmid, Ute
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.05.2022 Springer Nature B.V
Subjects:	Algorithms Arches Artificial Intelligence Computer Science Control Domains Logic programming Machine Learning Mechatronics Natural Language Processing (NLP) Robotics Simulation and Modeling Contrastive explanations Explainable AI Near miss examples Inductive logic programming Relational concepts
ISSN:	0885-6125, 1573-0565
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!