Design and Stability Analysis of Multi-Objective Ensemble Classifiers
Pourtaheri, Zeinab Khatoun (University of Birjand (Birjand, Iran). Department of Electrical and Computer Engineering)
Zahiri, Seyed Hamid (University of Birjand (Birjand, Iran). Department of Electrical and Computer Engineering)
Razavi, Seyed Mohammad (University of Birjand (Birjand, Iran). Department of Electrical and Computer Engineering)

Data:	2016
Resum:	In this paper a novel multi-objective optimization technique based on Inclined Planes Optimization algorithm (called MOIPO), is used to design an ensemble classifier. Diversity, ensemble size, and error rate are three objectives which are considered along designing the proposed ensemble classifier. The performance of designed ensemble classifier is tested on different kinds of benchmarks with nonlinear, overlapping class boundaries, and different feature space dimensions. Extensive experimental and comparative results on these data sets provided to show the performance of the proposed method, are better than ensemble designed by Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Another important aspect of this article is stability analysis of designed ensemble classifier. In fact, for the first time, the stability of a heuristic ensemble classifier is analyzed by using statistical method. For this aim, three regression models are investigated by applying F-test to find better model in each case. Due to the results of stability analysis, quadratic model is the best model for two datasets as representative of simple data and overlapped data.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Ensemble Classifier ; Heuristic Algorithms ; Multi-Objective Inclined Planes Optimization Methods ; Regression Models ; Stability Analysis
Publicat a:	ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 15 Núm. 3 (2016) , p. 32-47 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v15-n3-pourtaheri
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/321452
DOI: 10.5565/rev/elcvia.929

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