2017 Volume 3 Issue 1 Pages 1-10
To derive useful information from complicated data, many hybrid modeling strategies that combine nonparametric and parametric methods have been proposed. In this study, we propose a new hybrid modeling strategy that combines the random forest and the x-means methods using linear regression analysis. This strategy is referred to as XR regression.This study has three purposes: to improve the performance of a strategy of hybrid modeling using the random forest method, to determine an optimal class automatically using the x-means method, and to compare the prediction accuracy of this method with that of other existing methods.To determine the characteristics of XR regression, we compare its prediction accuracy with that of the existing methods using Monte Carlo simulations.The simulation results show that XR regression has a high performance in any situation, especially in data sets that include interaction effects.
