Design Ensemble Machine Learning Model for Breast Cancer Diagnosis

Sheau-Ling Hsieh, Sung-Huai Hsieh, Po-Hsun Cheng, Chi-Huang Chen, Kai-Ping Hsu, I-Shun Lee, Zhenyu Wang, Fei-Pei Lai

Research output: Contribution to journalArticle

27 Scopus citations

Abstract

In this paper, we classify the breast cancer of medical diagnostic data. Information gain has been adapted for feature selections. Neural fuzzy (NF), k-nearest neighbor (KNN), quadratic classifier (QC), each single model scheme as well as their associated, ensemble ones have been developed for classifications. In addition, a combined ensemble model with these three schemes has been constructed for further validations. The experimental results indicate that the ensemble learning performs better than individual single ones. Moreover, the combined ensemble model illustrates the highest accuracy of classifications for the breast cancer among all models.
Original languageEnglish
Pages (from-to)2841-2847
Number of pages7
JournalJournal of Medical Systems
Volume36
Issue number5
DOIs
StatePublished - Oct 2012

Keywords

  • Ensemble learning; Neural fuzzy; KNN; Quadratic classifier; Information gain

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    Hsieh, S-L., Hsieh, S-H., Cheng, P-H., Chen, C-H., Hsu, K-P., Lee, I-S., Wang, Z., & Lai, F-P. (2012). Design Ensemble Machine Learning Model for Breast Cancer Diagnosis. Journal of Medical Systems, 36(5), 2841-2847. https://doi.org/10.1007/s10916-011-9762-6