Ensemble Models with Trees and Rules

Abstract: In this article, we have proposed several approaches for post processing a large ensemble of prediction models or rules. The results from our simulations show that the post processing methods we have considered here are promising. We have used the techniques developed here for estimation of quantitative traits from markers, on the benchmark "Bostob Housing"data set and in some simulations. In most cases, the produced models had better prediction performance than, for example, the ones produced by the random forest or the rulefit algorithms.