Publication Details
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Author(s): I. Partalas, E. Hatzikos, G. Tsoumakas, I. Vlahavas.
Title: “Ensemble Selection for Water Quality Prediction”.
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Appeared in:
Proceedings of the 10th International Conference on Engineering Applications of Neural Networks, Thessaloniki, 2007. Abstract: This paper studies the greedy ensemble selection algorithm for ensembles of regression models. We explore two interesting parameters of this algorithm: a) the direction of search (forward, backward), and b) the performance evaluation dataset (training set, validation set) on a large ensemble (200 models) of neural networks and support vector machines. Experimental comparison of the different parameters are performed on an application domain with important social and commercial value: water quality monitoring. In specific we experiment on real data collected from an underwater sensor system.
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