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  • 标题:Hybrid bat-ant colony optimization algorithm for rule-based feature selection in health care
  • 本地全文:下载
  • 作者:Rafid Sagban ; Haydar A. Marhoon ; Raaid Alubady
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2020
  • 卷号:10
  • 期号:6
  • 页码:6655-6663
  • DOI:10.11591/ijece.v10i6.pp6655-6663
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:Rule-based classification in the field of health care using artificial intelligence provides solutions in decision-making problems involving different domains. An important challenge is providing access to good and fast health facilities. Cervical cancer is one of the most frequent causes of death in females. The diagnostic methods for cervical cancer used in health centers are costly and time-consuming. In this paper, bat algorithm for feature selection and ant colony optimization-based classification algorithm were applied on cervical cancer data set obtained from the repository of the University of California, Irvine to analyze the disease based on optimal features. The proposed algorithm outperforms other methods in terms of comprehensibility and obtains better results in terms of classification accuracy.
  • 关键词:Feature Selection;Detection Making;Bat Algorithm;Ant Colony Optimization;Rule-based Classification
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