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Diagnosing breast cancer based on support vector machines

  • H. X. Liu
  • , R. S. Zhang
  • , F. Luan
  • , X. J. Yao
  • , M. C. Liu
  • , Z. D. Hu
  • , B. T. Fan

研究成果: Article同行評審

123 引文 斯高帕斯(Scopus)

摘要

The Support Vector Machine (SVM) classification algorithm, recently developed from the machine learning community, was used to diagnose breast cancer. At the same time, the SVM was compared to several machine learning techniques currently used in this field. The classification task involves predicting the state of diseases, using data obtained from the UCI machine learning repository. SVM outperformed k-means cluster and two artificial neural networks on the whole. It can be concluded that nine samples could be mislabeled from the comparison of several machine learning techniques.

原文English
頁(從 - 到)900-907
頁數8
期刊Journal of Chemical Information and Computer Sciences
43
發行號3
DOIs
出版狀態Published - 5月 2003
對外發佈

UN SDG

此研究成果有助於以下永續發展目標

  1. Good health and well being
    Good health and well being

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