Wen-Ming Lee

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Breast cancer is a common to females worldwide. Today, technological advancements in cancer treatment innovations have increased the survival rates. Many theoretical and experimental studies have shown that a multiple classifier system is an effective technique for reducing prediction errors. This study compared the particle swarm optimizer (PSO) based(More)
Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification(More)
4135 Fig. 3 indicates that the computational cost of iterative GBF is significantly lower than those of greedy bit filling [3] and the algorithm in [2], particularly in cases of larger N and smaller b. For instance, when N = 512 and b = 6 is the case, R 1 varies from 88% to 98% along with η, whereas the value of R 2 is almost steadily 88%. For given values(More)
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