TY - CONF T1 - COMPARISON OF MASS APPRAISAL MODELS FOR EFFECTIVE PREDICTION OF PROPERTY VALUES T2 - Sustainable Multi-Sectoral Real Estate Development in Emerging Economies - the 16th African Real Estate Society Conference Y1 - 2016 A1 - Yacim, Joseph Awoamim A1 - Bosho , Douw Gert KW - accuracy KW - market values KW - mass appraisal models KW - predictions KW - properties AB -

There are a number of models that are used for mass appraisal of properties. However, the choice of a model is predicated on a number of criteria. One of these criteria is to compare models predictive accuracies that are reflected in minimum error of estimates. This study focuses on comparing predictive accuracies of mass appraisal models with a datasets of 3494 property transactions from the city of Cape Town, South Africa. Five mass appraisal models including back propagation trained artificial neural networks, multiple regression model, M5P tree, support vector machine optimise with sequential minimal optimisation and additive nonparametric regression were used for the simulations. Waikato Environment for Knowledge Analysis (WEKA) explorer; an open source data mining software was used to pre-processed property data to normalised values and model property prices. The analysis shows that BP trained artificial neural networks (BP-ANN) and M5P tree utilised in this study predicted better results with root mean squared error and mean absolute error within acceptable threshold of 5%. But M5P tree shows distinctiveness in predicted results between normalised and absolute values which require further examination. The other three mass appraisal models including multiple regression model, additive nonparametric regression and support vector machines with simulated minimal optimisation predicted RMSE that are higher than 5% acceptable threshold. With these results it is hereby recommended that mortgage lenders, valuation offices in South Africa, the rest of Africa and beyond should consider utilising BP-ANN in their mass appraisal predictions.
 

JA - Sustainable Multi-Sectoral Real Estate Development in Emerging Economies - the 16th African Real Estate Society Conference T3 - AfRES PB - African Real Estate Society CY - Adis Ababa, Ethiopia SP - 218-252 J1 - AfRES 2016 ID - oai:afres.id:afres2016_151 M3 - 10.15396/afres2016_151 ER -