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Feature Selection on Elite Hybrid Binary Cuckoo Search in Binary Label Classification
Computational and Mathematical Methods in Medicine Pub Date : 2021-05-12 , DOI: 10.1155/2021/5588385
Maoxian Zhao 1 , Yue Qin 1
Affiliation  

For the low optimization accuracy of the cuckoo search algorithm, a new search algorithm, the Elite Hybrid Binary Cuckoo Search (EHBCS) algorithm, is improved by feature weighting and elite strategy. The EHBCS algorithm has been designed for feature selection on a series of binary classification datasets, including low-dimensional and high-dimensional samples by SVM classifier. The experimental results show that the EHBCS algorithm achieves better classification performances compared with binary genetic algorithm and binary particle swarm optimization algorithm. Besides, we explain its superiority in terms of standard deviation, sensitivity, specificity, precision, and -measure.

中文翻译:

二元标签分类中精英混合二元布谷鸟搜索的特征选择

针对布谷鸟搜索算法优化精度低的问题,通过特征加权和精英策略改进了一种新的搜索算法——精英混合二元布谷鸟搜索(EHBCS)算法。EHBCS 算法设计用于一系列二进制分类数据集的特征选择,包括 SVM 分类器的低维和高维样本。实验结果表明,与二元遗传算法和二元粒子群优化算法相比,EHBCS算法具有更好的分类性能。此外,我们解释标准偏差,敏感性,特异性,精度和方面的优越性-措施。
更新日期:2021-05-12
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