Proefschrift
Information-theoretic partition-based models for interpretable machine learning
In this dissertation, we study partition-based models that can be used both for interpretable predictive modeling and for understanding data via interpretable patterns.
- Auteur
- L. Yang
- Datum
- 20 september 2024
- Links
- Thesis in Leiden Repository
Specifically, we study probabilistic rule-based models for multi-class classification and histogram models for discretization, explanatory data analysis, and conditional mutual information estimation.