- author = "Wenbin Pei and Bing Xue and Lin Shang and Mengjie Zhang",
- title = "Genetic programming for high-dimensional imbalanced classification with a new fitness function and program reuse mechanism",
- journal = "Soft Computing",
- year = "2020",
- volume = "24",
- number = "23",
- pages = "18021--18038",
- month = dec,
- note = "Special Issue Dedicated to the 3rd International Conference {"}Numerical Computations: Theory and Algorithms, NUMTA 2019{"} June 15-21, 2019, Isola Capo Rizzuto, Italy",
- keywords = "genetic algorithms, genetic programming, Fitness function, Class imbalance, High dimensionality",
- ISSN = "1432-7643",
-
DOI = "
doi:10.1007/s00500-020-05056-7",
- abstract = "Genetic programming (GP) has been successfully applied to classification. However, GP may evolve biased classifiers when encountering the problem of class imbalance. These biased classifiers are often not reliable to be applied to some real-world applications. High dimensionality makes it more difficult for classifiers to effectively separate the majority class and the minority class. The use of GP to handle the joint effect of high dimensionality and class imbalance has not been heavily investigated. In this paper, we propose a GP approach to high-dimensional imbalanced classification, with the goals of increasing the classification performance as well as saving training time. To achieve this goal, a new fitness function is developed to solve the problem of class imbalance, and moreover, a strategy is proposed to reuse previous good GP individuals for improving efficiency. The proposed method is examined on ten high-dimensional imbalanced datasets. Experimental results show that, for high-dimensional imbalanced classification, the proposed method generally outperforms other GP methods and traditional classification algorithms using sampling methods to solve the problem of class imbalance.",
-
notes = "Two issues in December 2020
Affiliations
School of Engineering and Computer Science, Victoria University of Wellington, P.O. Box 600, Wellington, 6140, New Zealand
Wenbin Pei, Bing Xue & Mengjie Zhang
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210093, China
