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  • 标题:An Enhanced Breast Cancer Diagnosis Scheme based on Two-Step-SVM Technique
  • 本地全文:下载
  • 作者:Ahmed Hamza Osman
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2017
  • 卷号:8
  • 期号:4
  • DOI:10.14569/IJACSA.2017.080423
  • 出版社:Science and Information Society (SAI)
  • 摘要:This paper proposes an automatic diagnostic method for breast tumour disease using hybrid Support Vector Machine (SVM) and the Two-Step Clustering Technique. The hybrid technique is aimed at improving the diagnostic accuracy and reducing diagnostic miss-classification, thereby solving the classification problems related to Breast Tumour. To distinguish the hidden patterns of the malignant and benign tumours, the Two-Step algorithm and SVM have been combined and employed to differentiate the incoming tumours. The developed hybrid method enhances the accuracy by 99.1% when examined on the UCI-WBC data set. Moreover, in terms of evaluation measures, it has been shown experimentally results that the hybrid method outperforms the modern classification techniques for breast cancer diagnosis.
  • 关键词:Two-Step Clustering; Breast Cancer; SVM classification; Diagnosis; Tumors
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