GA-Based Feature Selection Method for Imbalanced Data with Application in Radio Signal Recognition
- 10.1080/18756891.2015.1129577How to use a DOI?
- feature selection, genetic algorithm, imbalanced data, radio signal recognition, ground-air communication
This paper presents an improved genetic algorithm (GA) based feature selection method for imbalanced data classification, which is then applied to radio signal recognition of ground-air communication. The proposed method improves the fitness function while SVM is selected as the classifier due to its good classification performance. This method is firstly evaluated using several benchmark datasets and experimental results show that the proposed method outperforms the original GA-based feature selection method now that it not only reduces the feature dimension effectively, but also improves the precision of the minor class. Finally, the proposed method is applied to a real world application in radio signal recognition of ground-air communication, which again shows comparatively better performance.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Limin Du AU - Yang Xu AU - Jun Liu AU - Fangli Ma PY - 2015 DA - 2015/12/01 TI - GA-Based Feature Selection Method for Imbalanced Data with Application in Radio Signal Recognition JO - International Journal of Computational Intelligence Systems SP - 39 EP - 47 VL - 8 IS - Supplement 1 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2015.1129577 DO - 10.1080/18756891.2015.1129577 ID - Du2015 ER -