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ANNS are efficient and objective classification methods in subject classification. It is an information processing system whose design was inspired by the structure and functioning of neuron in biology. Thus, they have been successfully applied to the numerous classification fields. Sometimes, however, classifications do not match the real world, and are subjected to errors. These problems are caused...
In subject classification, principal component analysis is implemented as an objective and practical validation method, but the real data calculation shows that the result of principal component analysis is not always complied with the real situation. Sometimes, it can be totally messed up. Some problems exist regarding to this classification, while these problems are caused by the nature of principal...
In subject classification, artificial neural networks (ANNS) are efficient and objective classification methods. Thus, they have been successfully applied to the numerous classification fields. Sometimes, however, classifications do not match the real world, and are subjected to errors. These problems are caused by the nature of ANNS. We discuss these on multilayer perceptron neural networks. By studying...
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