Greedy regression ensemble selection: Theory and an application to water quality prediction

This paper studies the greedy ensemble selection family of algorithms for ensembles of regression models. These algorithms search for the globally best subset of regresmaking local greedy decisions for changing the current subset. We abstract the key points of the greedy ensemble selection algorithms and present a general framework, which is applied to an application domain with important social and commercial value: water quality prediction.

• Type: Journal
• Year: 2008
• Where: ISCI
• Authors: Ioannis Partalas, Grigorios Tsoumakas, Evaggelos V. Hatzikos, Ioannis P. Vlahavas
• Keywords: Ensemble Selection Family, Greedy Ensemble Selection, ISCI 2008, Local Greedy Decisions