Streaming multi-layer ensemble selection using dynamic genetic algorithm.

Luong, Anh Vu; Nguyen, Tien Thanh; Liew, Alan Wee-Chung

Abstract

In this study, we introduce a novel framework for non-stationary data stream classification problems by modifying the Genetic Algorithm to search for the optimal configuration of a streaming multi-layer ensemble. We aim to connect the two sub-fields of non-stationary stream classification and evolutionary dynamic optimization. First, we present Streaming Multi-layer Ensemble (SMiLE) - a novel classification algorithm for nonstationary data streams which comprises multiple layers of different classifiers. Second, we develop an ensemble selection method to obtain an optimal subset of classifiers for each layer of SMiLE. We formulate the selection process as a dynamic optimization problem and then solve it by adapting the Genetic Algorithm to the stream setting, generating a new classification framework called SMiLE_GA. Finally, we apply the proposed framework to address a real-world problem of insect stream classification, which relates to the automatic recognition of insects through optical sensors in real-time. The experiments showed that the proposed method achieves better prediction accuracy than several state-of-the-art benchmark algorithms for non-stationary data stream classification.

Citation

LUONG, A.V., NGUYEN, T.T. and LIEW, A.W.-C. 2021. Streaming multi-layer ensemble selection using dynamic genetic algorithm. In Zhou, J., Salvado, O., Sohel, F., Borges, P. and Wang, S. (eds.). Proceedings of 2021 Digital image computing: techniques and applications (DICTA 2021), 29 November - 1 December 2021, Gold Coast, Australia. Piscataway: IEEE [online], article 9647220. Available from: https://doi.org/10.1109/dicta52665.2021.9647220

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2021 Digital image computing: techniques and applications (DICTA 2021)
• Start Date: Nov 29, 2021
• End Date: Dec 1, 2021
• Acceptance Date: Sep 13, 2021
• Online Publication Date: Dec 23, 2021
• Publication Date: Dec 31, 2021
• Deposit Date: Jan 13, 2022
• Publicly Available Date: Jan 13, 2022
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• ISBN: 9781665417105
• DOI: https://doi.org/10.1109/dicta52665.2021.9647220
• Keywords: Ensemble method; Multi-layer ensemble; Genetic algorithm
• Public URL: https://rgu-repository.worktribe.com/output/1563807