The application of boosting technique to regression problems has received relatively little attention in contrast to research aimed at classification problems. This letter describes a new boosting algorithm, AdaBoost.RT, for regression problems. Its idea is in filtering out the examples with the relative estimation error that is higher than the preset threshold value, and then following the Ada...

Reliable estimations of sediment yields are very important for investigations river morphology and water resources management. Nowadays, soft computing methods helpful famous regarding the accurate estimation loads. The present study checked applicability radial M5 tree (RM5Tree) model to accurately estimate using daily inputs snow cover fraction, air temperature, evapotranspiration effective r...

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This study investigates the accuracy of three different techniques with periodicity component for estimating monthly lake levels. The are multivariate adaptive regression splines (MARS), least-square support vector (LSSVR), and M5 model tree (M5-tree). Data from Lake Michigan, located in USA, is used analysis. In first stage modeling, were applied to forecast level fluctuations up 8 months ahea...

A mixture of local experts consists of a set of specialized models each of which is responsible for a particular local region of input space. Many algorithms in this class, for example M5 model tree, are sub-optimal (greedy). An algorithm for building optimal local mixtures of regression experts is proposed, and compared to MLP ANN on a number of cases.