Titlebook: Intelligent Data Engineering and Automated Learning - IDEAL 2007; 8th International Co Hujun Yin,Peter Tino,Xin Yao Conference proceedings

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Support Function Machinesachines (SVM) and procedural neural networks (PNN) are compared in solving time series and they inspire the creation of SFM. SFM aims to extend the support vectors to spatiotemporal domain, in which each component of vectors is a function with respect to time. In the view of the function, SFM transf

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Different Bayesian Network Models in the Classification of Remote Sensing Imagesof Bayesian networks as: Naive Bayes (NB), Tree Augmented Naive Bayes (TAN) and General Bayesian Networks (GBN), are applied to the classification of hyperspectral data. In addition, several Bayesian multi-net models: TAN multi-net, GBN multi-net and the model developed by Gurwicz and Lerner, TAN-Ba

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Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensemblesarning. These error curves are parametrized in terms of the probability that a given instance is misclassified by one of the predictors in the ensemble. Out of bootstrap estimates of these probabilities can be used to model generalization error curves using only information from the training data. S