A procedure for detecting outliers in regression problems is proposed. It is based on information provided by boosting regression trees. The key idea is to select the most frequently resampled observation along the boosting iterations and reiterate after removing it. The selection criterion is based on Tchebychev’s inequality applied to the maximum over the boosting iterations of ...

Artificial Neural Network (ANN) model along with Back Propagation Algorithm (BPA) has been applied in many fields, especially in hydrology and water resources management to simulate or forecast rainfall runoff process, discharge and water level time series, and other hydrological variables. Several researches have recently been focusing to compare the applicability of ANN model with other theor...

physiographic characteristics and climatic conditions are factors which contributing to river flow regime and understanding of relations between these factors and river flow in a basin result in its application for the ungauged sub-basins river flow prediction. in this research the relation between physiographic and climatic parameters of golestan province and rivers flow were examined by appli...

In this paper, we model an optimal regression tree through a continuous optimization problem, where compromise between prediction accuracy and both types of sparsity, namely local global, is sought. Our approach can accommodate important desirable properties for the task, such as cost-sensitivity fairness. Thanks to smoothness predictions, derive explanations on predictor variables. The computa...