I. Partalas, E. Hatzikos, G. Tsoumakas, I. Vlahavas (2007) “Ensemble Selection for Water Quality Prediction”, Proceedings of the 10th International Conference on Engineering Applications of Neural Networks (EANN 2007), pp 428-435, Thessaloniki, Greece, August 29-31, 2007.

Author(s): I. Partalas, E. Hatzikos, Grigorios Tsoumakas, I. Vlahavas

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Appeared In: 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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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.