Reframing in context: A systematic approach for model reuse in machine learning-Reference-Cited by-同舟云学术

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Reframing in context: A systematic approach for model reuse in machine learning

Published:2016-11-15 Issue:5 Volume:29 Page:551-566
ISSN:1875-8452
Container-title:AI Communications
language:
Short-container-title:AIC

Author:

Hernández-Orallo José¹,Martínez-Usó Adolfo¹,Prudêncio Ricardo B.C.²,Kull Meelis³,Flach Peter³,Farhan Ahmed Chowdhury⁴,Lachiche Nicolas⁴

Affiliation:

1. DSIC, Universitat Politècnica de València, Spain. E-mails: jorallo@dsic.upv.es, admarus@dsic.upv.es

2. Centro de Informática, Universidade Federal de Pernambuco, Recife (PE), Brazil. E-mail: rbcp@cin.ufpe.br

3. Department of Computer Science, University of Bristol, UK. E-mails: meelis.kull@bristol.ac.uk, peter.flach@bristol.ac.uk

4. ICube, Université de Strasbourg, France. E-mails: cfahmed@unistra.fr, nicolas.lachiche@unistra.fr

Publisher

IOS Press

Subject

Artificial Intelligence

Reference65 articles.

1. Towards a Better Understanding of Context and Context-Awareness

2. Context-Aware Recommender Systems

3. C.F. Ahmed, N. Lachiche, C. Charnay and A. Braud, Reframing continuous input attributes, in: IEEE Intl. Conf. Tools with Artificial Intelligence (ICTAI-2014), 2014, pp. 31–38.

4. Learning from noisy examples;Angluin;Machine Learning,1988

5. Tuning data mining methods for cost-sensitive regression: A study in loan charge-off forecasting;Bansal;J. Management Inf. Systems,2008

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