Quantitative study on the generalization error of multiple classifier systems

Multiple classifier system (MCS) has been one of the hot research topics in machine learning field. A MCS merges an ensemble of different or same type of classifiers together to enhance the problem solving performance of machine learning. However, the choice of the number of classifiers and the fusi...

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Hauptverfasser:	Ng, W.W.Y., Chan, A.P.F., Yeung, D.S., Tsang, E.C.C.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Artificial neural networks Bagging Classification tree analysis Classifier Performance Assessment Ensemble of Classifiers Fusion of Classifiers and Generalization Error Intrusion detection Machine learning Mean square error methods Model Evaluation Multiple Classifier System Problem-solving Radial basis function networks Radial Basis Function Neural Network (RBFNN) Support vector machine classification Support vector machines
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