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- W2148796619 abstract "To improve the performance of secondary structure prediction, a multi-SVM ensemble was applied, bagging was used to resample the training dataset. The SVM ensemble was made of two-layer, one is composed by three SVM network decided by winner-take-all, the other is a ensemble network composed of five classifier decided by majority voting. Seven-fold cross-validation test on RS126 dataset indicated that the multi-SVM ensemble could achieve better performance on secondary structure prediction." @default.
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- W2148796619 date "2010-08-01" @default.
- W2148796619 modified "2023-09-26" @default.
- W2148796619 title "Protein secondary structure prediction based on multi-SVM ensemble" @default.
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- W2148796619 doi "https://doi.org/10.1109/icicip.2010.5564201" @default.
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