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19 October 2023 An evolving ensembles method based on genetic programming and whale optimization algorithm for imbalanced datasets
Jingchao Ji, Xiaobo Li
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Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127092E (2023) https://doi.org/10.1117/12.2684911
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China
Abstract
Genetic Programming (GP) algorithm has been successfully applied to classification tasks for many years, with a long history and remarkable effects. It is worth noting that GP tends to evolve biased classifiers when it is used for class imbalanced datasets. Biased classifiers are often unreliable and will seriously affect the classification performance. In addition, when GP is used to train the model to adapt to the high-dimensional imbalanced datasets, it is easy to be affected by the majority class and ignore the existence of the minority class. Therefore, classification tasks based on GP in high-dimensional and imbalanced datasets need to be further studied. In this paper, we propose a GP approach for imbalance classification tasks with the aim of improving the classification performance and minimizing the time consumption, named HGPWOA. A multi-objectivization fitness function is adopted to solve the problem, supplemented by Whale Optimization Algorithm (WOA) for feature selection, and then feature augmentation strategy is adopted to improve the classification efficiency. The method was tested on five imbalanced datasets. The experimental results show that this method is superior to the traditional classification algorithms, which provides a new way to study the class imbalance problems.
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Jingchao Ji and Xiaobo Li "An evolving ensembles method based on genetic programming and whale optimization algorithm for imbalanced datasets", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127092E (19 October 2023); https://doi.org/10.1117/12.2684911
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KEYWORDS
Evolutionary algorithms
Evolutionary optimization
Feature selection
Machine learning
Computer programming
Mathematical optimization
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