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Kernel-based naive bayes classifier for breast cancer prediction

Nahar, Jesmin, Chen, Yi-Ping Phoebe and Ali, Shawkat 2007, Kernel-based naive bayes classifier for breast cancer prediction, Journal of biological systems, vol. 15, no. 1, pp. 17-25.

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Title Kernel-based naive bayes classifier for breast cancer prediction
Author(s) Nahar, Jesmin
Chen, Yi-Ping Phoebe
Ali, Shawkat
Journal name Journal of biological systems
Volume number 15
Issue number 1
Start page 17
End page 25
Publisher World Scientific Publishing Company
Place of publication Singapore
Publication date 2007-03
ISSN 0218-3390
Keyword(s) Breast Cancer Prediction
Classification
Kernel-Based Naive Bayes Classifier
Summary The classification of breast cancer patients is of great importance in cancer diagnosis. Most classical cancer classification methods are clinical-based and have limited diagnostic ability. The recent advances in machine learning technique has made a great impact in cancer diagnosis. In this research, we develop a new algorithm: Kernel-Based Naive Bayes (KBNB) to classify breast cancer tumor based on memography data. The performance of the proposed algorithm is compared with that of classical navie bayes algorithm and kernel-based decision tree algorithm C4.5. The proposed algorithm is found to outperform in the both cases. We recommend the proposed algorithm could be used as a tool to classify the breast patient for early cancer diagnosis.
Language eng
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©World Scientific Publishing Company
Persistent URL http://hdl.handle.net/10536/DRO/DU:30007570

Document type: Journal Article
Collection: School of Engineering and Information Technology
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