Support vector machine for outlier detection in breast cancer survivability prediction

Jaree THONGKAM, Guandong XU, Yanchun ZHANG, Fuchun HUANG

Research output: Chapter in Book/Report/Conference proceedingChapters

35 Citations (Scopus)

Abstract

Finding and removing misclassified instances are important steps in data mining and machine learning that affect the performance of the data mining algorithm in general. In this paper, we propose a C-Support Vector Classification Filter (C-SVCF) to identify and remove the misclassified instances (outliers) in breast cancer survivability samples collected from Srinagarind hospital in Thailand, to improve the accuracy of the prediction models. Only instances that are correctly classified by the filter are passed to the learning algorithm. Performance of the proposed technique is measured with accuracy and area under the receiver operating characteristic curve (AUC), as well as compared with several popular ensemble filter approaches including AdaBoost, Bagging and ensemble of SVM with AdaBoost and Bagging filters. Our empirical results indicate that C-SVCF is an effective method for identifying misclassified outliers. This approach significantly benefits ongoing research of developing accurate and robust prediction models for breast cancer survivability. Copyright © 2008 Springer-Verlag Berlin Heidelberg.

Original languageEnglish
Title of host publicationAdvanced web and network technologies, and applications: APWeb 2008 International Workshops, BIDM, IWHDM, and DeWeb Shenyang, China, April 26-28, 2008, Shenyang, China Revised Papers
EditorsYoshiharu ISHIKAWA, Jing HE, Guandong XU, Yong SHI, Guangyan HUANG, Chaoyi PANG, Qing ZHANG, Guoren WANG
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages99-109
ISBN (Electronic)9783540893769
ISBN (Print)354089375X, 9783540893752
DOIs
Publication statusPublished - 2008

Citation

Thongkam, J., Xu, G., Zhang, Y., & Huang, F. (2008). Support vector machine for outlier detection in breast cancer survivability prediction. In Y. Ishikawa, J. He, G. Xu, Y. Shi, G. Huang, C. Pang, Q. Zhang, & G. Wang (Eds.), Advanced web and network technologies, and applications: APWeb 2008 International Workshops, BIDM, IWHDM, and DeWeb Shenyang, China, April 26-28, 2008, Shenyang, China Revised Papers (pp. 99-109). Springer. https://doi.org/10.1007/978-3-540-89376-9_10

Keywords

  • Outlier detection system
  • C-Support Vector Classification Filter (C-SVCF)
  • Breast cancer survivability

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