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- W2009482011 abstract "Data-mining algorithms have been used in many classification problems. Among them, the decision tree (DT), back-propagation network (BPN), and support vector machine (SVM) are popular and can be applied to various areas. Nevertheless, different problems may require different parameter values when applying DT, BPN or SVM. If parameter values are not set well, results may turn out to be unsatisfactory. Further, a dataset may contain many features; however, not all features are beneficial for classifications. Therefore, a scatter search (SS) approach is proposed to obtain the better parameters and select the beneficial subset of features to attain better classification results." @default.
- W2009482011 created "2016-06-24" @default.
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- W2009482011 date "2011-01-01" @default.
- W2009482011 modified "2023-10-17" @default.
- W2009482011 title "Enhancing the classification accuracy by scatter-search-based ensemble approach" @default.
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- W2009482011 doi "https://doi.org/10.1016/j.asoc.2010.01.024" @default.
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