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  • 标题:SMO classification for cervical cancer dataset by applying various kernels
  • 本地全文:下载
  • 作者:G.Ayyappan ; K.SivaKumar
  • 期刊名称:Indian Journal of Computer Science and Engineering
  • 印刷版ISSN:2231-3850
  • 电子版ISSN:0976-5166
  • 出版年度:2019
  • 卷号:10
  • 期号:1
  • 页码:28-30
  • DOI:10.21817/indjcse/2019/v10i1/191001011
  • 出版社:Engg Journals Publications
  • 摘要:This research work presents a decision making of healthcare operational system by usingmachine learning classifiers algorithm to predict the decision making in comparison to the actual decisionmaking. This model may help to doctor for making the best decisions. This model helps us to prediction ofindicators/diagnosis of cervical cancer. This study explains utilization of machine learning algorithms indetermination of medical operation methods. This dataset focuses on the prediction ofindicators/diagnosis of cervical cancer. The results show that SMO in RBF Kernel parameter for thiscase study generates highest accuracy level of 87.5%.
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