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The subcellular location plays a pivotal role in the functionality of proteins. In this paper we develop a multi-stage linear classifier fusion system based on Efron's bootstrap sampling for predicting subcellular locations of yeast proteins. Three different types of classifiers, i.e. the Naive Bayes (NB) classifier, radial basis function (RBF) network, and multilayer perceptron (MLP), are utilized...
The subcellular location plays a pivotal role in the functionality of proteins. In this paper we develop a multi-stage linear classifier fusion system based on Efron's bootstrap sampling for predicting subcellular locations of yeast proteins. Three different types of classifiers, i.e. the Naive Bayes (NB) classifier, radial basis function (RBF) network, and multilayer perceptron (MLP), are utilized...
We introduce a non-parametric linear decision fusion called perceptron average (PA) for breast cancer diagnosis. We concretely compare the accuracy between both two fusion strategies for breast cancer diagnosis. The PA fusion demonstrates a higher overall diagnostic accuracy versus the weighted average fusion, and the PA fusion method also exhibits a better capability of generalization when a casualty...
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