We propose a new ensemble classification algorithm, named super random subspace ensemble (Super RaSE), to tackle the … sparse classification problem. The proposed algorithm is motivated by the random subspace ensemble algorithm (RaSE). The RaSE …

voting ensemble method with a decision tree (DT) with experimental data on US restaurant between 1980 and 2017. According to … the voting ensemble of business failure prediction. Three models, including an entire period (EP) model, an economic … prediction models. And second, by using an ensemble model with a DT, it has improved both the interpretability of the results and …

This paper applies component-wise boosting to the topic of regional economic forecasting. Component-wise boosting is a … combination with a large data set of monthly indicators, we show that boosting is generally doing a very good job in regional …, boosting outperforms our benchmark model for all the three regions considered. We also find that indicators that mirror the …

based on the ideas of mixed models. Specifically, we propose a semiparametric mixed model with boosting to recover the …

inequality constraints on basis coefficients by boosting techniques. Therefore, recently developed componentwise boosting methods …

of the penalized estimator, which is based on a new boosting method, allows to select variables. Real world data and …

variables and the problems of selection of smoothing parameters. Generalized additive model boosting circumvents these problems …