Towards Optimally Diverse Randomized Ensembles of Neural Networks
Anna Martin
Broschiertes Buch

Towards Optimally Diverse Randomized Ensembles of Neural Networks

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The concept of ensemble learning has become exceptionally popular over the last couple decades due to the ability of a group of base classifiers trained for the same problem to often demonstrate higher accuracy than that of a single model. The main idea behind such an ensemble of models, which outperforms a single model, is to combine a set of diverse classifiers. This work concentrates on neural networks as base classifiers and explores the influence of the parameters of neural networks, whose randomization leads to generating diverse ensembles with better generalisation ability compared to a...