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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Kernel-based naive bayes classifier for breast cancer prediction
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.
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eng
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080199 Artificial Intelligence and Image Processing not elsewhere classified
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