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Meta-Mining Evaluation Framework : A large scale proof of concept on Meta-Learning

Raynaut, William and Soulé-Dupuy, Chantal and Vallés-Parlangeau, Nathalie Meta-Mining Evaluation Framework : A large scale proof of concept on Meta-Learning. (2016) In: 29th Australian Conference on Artificial Intelligence 2016 (AI 2016), 5 December 2016 - 8 December 2016 (Hobart, Australia).

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Official URL: https://doi.org/10.1007/978-3-319-50127-7_18

Abstract

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)
Additional Information:Thanks to Springer editor. This papers appears in Volume 9992 of Lecture Notes in Computer Science ISSN : 0302-9743 ISBN: 978-3-319-50126-0 The original PDF is available at: https://link.springer.com/chapter/10.1007/978-3-319-50127-7_18
HAL Id:hal-01692700
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:12 Jan 2018 15:15

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