Raynaut, William, Soulé-Dupuy, Chantal and Vallès-Parlangeau, Nathalie (2016) Meta-Mining Evaluation Framework : A large scale proof of concept on Meta-Learning. In: 29th Australian Conference on Artificial Intelligence 2016 (AI 2016).

[thumbnail of assistant_17373020_3205211763_0.pdf]
Download (1MB) | Preview


This paper aims to provide a unified framework for the evaluation and comparison of the many emergent meta-mining techniques. This framework is illustrated on the case study of the meta-learning problem in a large scale experiment. The results of this experiment are then explored through hypothesis testing in order to provide insight regarding the performance of the different meta-learning schemes, advertising the potential of our approach regarding meta-level knowledge discovery.

Item Type: Conference or Workshop Item (Paper)
Language: English
Date: 2016
Uncontrolled Keywords: Meta-mining - Meta-learning - Evaluation criterion - Hypothesis testing - Knowledge discovery
Divisions: Institut de Recherche en Informatique de Toulouse
Site: UT1
Date Deposited: 28 Mar 2019 15:36
Last Modified: 02 Apr 2021 15:59
URI: https://publications.ut-capitole.fr/id/eprint/29132
View Item


Downloads per month over past year