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In many ‘real-world’ applications, a classification of large data sets, which are often also imbalanced, is difficult due to the small, but usually more interesting classes. In this study, a large data set, forest cover type classes, which is actually multi-class classification defined with seven imbalanced classes and used as a resource inventory information was analyzed and evaluated. The data set...
For aggregation to be effective the component artificial neural networks (ANNs) must be as accurate and diverse as possible, an improved Bagging neural network ensemble algorithm is proposed to cope with this problem. The Euclidean distances between two arbitrary samples of the original training set are analyzed, the training subsets of component ANNs are distilled from this set then. The subsets...
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