Zapis dokaza metode
Explainable Decision Tree
An Explainable Decision Tree is a classification or regression tree deliberately grown to be shallow, readable, and auditable — producing a finite set of if-then rules that a human can verify without additional tools. It sits at the intersection of predictive modelling and Explainable AI (XAI), chosen when stakeholders must understand and trust every prediction the model makes.
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Explainable Decision Tree (Interpretable Rule-Based Classification and Regression Tree)
Taksonomski zapis metode · ml-model / machine-learning
- Breiman, L., Friedman, J., Olshen, R. A., & Stone, C. J. (1984). Classification and Regression Trees. Wadsworth & Brooks/Cole. · ISBN 978-0-412-04841-8
- Rudin, C. (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence, 1(5), 206–215. · DOI 10.1038/s42256-019-0048-x
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