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Open AccessArticle

A Weighted Ensemble Learning Algorithm Based on Diversity Using a Novel Particle Swarm Optimization Approach

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Department of Management Engineering, Fujian Business University, Fuzhou 350012, China
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Information Technology Center, Fujian Business University, Fuzhou 350012, China
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Department of Industrial Engineering and Management Engineering, National Tsing Hua University, Hsinchu 300, Taiwan
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Department of Finance, Fujian Business University, Fuzhou 350012, China
*
Author to whom correspondence should be addressed.
Algorithms 2020, 13(10), 255; https://doi.org/10.3390/a13100255
Received: 18 August 2020 / Revised: 22 September 2020 / Accepted: 1 October 2020 / Published: 9 October 2020
(This article belongs to the Special Issue Classification and Regression in Machine Learning)
In ensemble learning, accuracy and diversity are the main factors affecting its performance. In previous studies, diversity was regarded only as a regularization term, which does not sufficiently indicate that diversity should implicitly be treated as an accuracy factor. In this study, a two-stage weighted ensemble learning method using the particle swarm optimization (PSO) algorithm is proposed to balance the diversity and accuracy in ensemble learning. The first stage is to enhance the diversity of the individual learner, which can be achieved by manipulating the datasets and the input features via a mixed-binary PSO algorithm to search for a set of individual learners with appropriate diversity. The purpose of the second stage is to improve the accuracy of the ensemble classifier using a weighted ensemble method that considers both diversity and accuracy. The set of weighted classifier ensembles is obtained by optimization via the PSO algorithm. The experimental results on 30 UCI datasets demonstrate that the proposed algorithm outperforms other state-of-the-art baselines. View Full-Text
Keywords: ensemble learning; diversity; machine learning; particle swarm optimization algorithm; weighted ensemble ensemble learning; diversity; machine learning; particle swarm optimization algorithm; weighted ensemble
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You, G.-R.; Shiue, Y.-R.; Yeh, W.-C.; Chen, X.-L.; Chen, C.-M. A Weighted Ensemble Learning Algorithm Based on Diversity Using a Novel Particle Swarm Optimization Approach. Algorithms 2020, 13, 255.

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