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Problem Transformation Methods with Distance-Based Learning for Multi-Target Regression
2020
Multi-target regression is a special subset of supervised machine learning problems. Problem transformation methods are used in the field to improve the performance of basic methods. The purpose of this article is to test the use of recently popularized distance-based methods, the minimal learning machine (MLM) and the extreme minimal learning machine (EMLM), in problem transformation. The main advantage of the full data variants of these methods is the lack of any meta-parameter. The experimental results for the MLM and EMLM show promising potential, emphasizing the utility of the problem transformation especially with the EMLM. peerReviewed
Vers un environnement informatisé d'évaluation de la qualité ergonomique d'interfaces multimédia : Étude exploratoire
2000
Our objective is to encourage the human-computer interface designers to be more interested in the uses made of their product by taking into account to a higher degree the human-factor in the testing phase which often is too focused on technical aspects. We want to facilitate the integration of the user as a source of evaluation during the testing phase. Our aim is to offer the designer a software environment of practical tests that allow them to have their own products evaluated by their users. We undertook an experiment to explore the feasibility of this project.
Vers un environnement informatisé d'évaluation de la qualité ergonomique d'interfaces multimédia : Étude exploratoire
2000
Our objective is to encourage the human-computer interface designers to be more interested in the uses made of their product by taking into account to a higher degree the human-factor in the testing phase which often is too focused on technical aspects. We want to facilitate the integration of the user as a source of evaluation during the testing phase. Our aim is to offer the designer a software environment of practical tests that allow them to have their own products evaluated by their users. We undertook an experiment to explore the feasibility of this project.