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

Research output: Contribution to journalArticlepeer-review

119 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)900-907
Number of pages8
JournalJournal of Chemical Information and Computer Sciences
Issue number3
Publication statusPublished - May 2003
Externally publishedYes


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