1st Edition
Machine Learning Meets Discourse Algorithms, Performance, and Interpretation
By Dennis Tay
Copyright 2027
178 Pages
10 B/W Illustrations
by
Routledge
Tay explores the Performance-Interpretability Trade-off (PIT) as a critical tension in AI and machine learning, and shows its distinctive form in discourse analysis where predictive success and interpretive meaning are inseparable.
Rather than treating PIT as a technical obstacle, this book reframes it as a site of conceptual negotiation and theoretical innovation. It introduces constructs such... Read more
Chapter 1. Introduction Chapter 2. The Performance–Interpretability Trade-off Chapter 3. Quantification Schemes Chapter 4. The Elasticity of Performance and Interpretability Chapter 5. Discourse Fingerprinting through Comparative Classifier Performance Chapter 6 Conclusion
Biography
Dennis Tay is Professor at the Division of Humanities, The Hong Kong University of Science and Technology, Hong Kong. He is trained in linguistics and computational mathematics. He is Co-Editor-in-Chief of Metaphor and the Social World and Associate Editor of Metaphor and Symbol, among other editorial board memberships.
