In this article we study the theoretical properties of Three-way Decision (TWD) based Machine Learning, from the perspective of Computational Learning Theory, as a first attempt to bridge the gap between Machine Learning theory and Uncertainty Representation theory. Drawing on the mathematical theory of orthopairs, we provide a generalization of the PAC learning framework to the TWD setting, and we use this framework to prove a generalization of the Fundamental Theorem of Statistical Learning. We then show, by means of our main result, a connection between TWD and selective prediction.

Campagner, A., Ciucci, D. (2022). Three-way Learnability: A Learning Theoretic Perspective on Three-way Decision. In Proceedings of the 17th Conference on Computer Science and Intelligence Systems, FedCSIS 2022 (pp.243-246). Polish Information Processing Society [10.15439/2022F18].

Three-way Learnability: A Learning Theoretic Perspective on Three-way Decision

Campagner A.
;
Ciucci D.
2022

Abstract

In this article we study the theoretical properties of Three-way Decision (TWD) based Machine Learning, from the perspective of Computational Learning Theory, as a first attempt to bridge the gap between Machine Learning theory and Uncertainty Representation theory. Drawing on the mathematical theory of orthopairs, we provide a generalization of the PAC learning framework to the TWD setting, and we use this framework to prove a generalization of the Fundamental Theorem of Statistical Learning. We then show, by means of our main result, a connection between TWD and selective prediction.
No
paper
learning theory; three-way decision; machine learning; uncertainty management
English
17th Conference on Computer Science and Intelligence Systems, FedCSIS 2022 - 4 September 2022through 7 September 2022
978-83-962423-9-6
Campagner, A., Ciucci, D. (2022). Three-way Learnability: A Learning Theoretic Perspective on Three-way Decision. In Proceedings of the 17th Conference on Computer Science and Intelligence Systems, FedCSIS 2022 (pp.243-246). Polish Information Processing Society [10.15439/2022F18].
Campagner, A; Ciucci, D
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/401876
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