A multi-agent system to assist with real estate appraisals using bagging ensembles

Abstract

The multi-agent system for real estate appraisals MAREA was extended to include aggregating agents, which could create ensemble models applying the bagging approach, was presented in the paper. The major part of the study was devoted to investigate to what extent bagging approach could lead to the improvement of the accuracy machine learning regression models. Four algorithms implemented in the KEEL tool, including linear regression, decision trees for regression, support vector machines, and artificial neural network of MLP type, were used in the experiments. The results showed that bagging ensembles ensured higher prediction accuracy than single models. © 2009 Springer Berlin Heidelberg.