Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics

Antipov, Evgeny and Pokryshevskaya, Elena (2010): Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics.

Abstract

To the best knowledge of authors, the use of Random forest as a potential technique for residential estate mass appraisal has been attempted for the first time. In the empirical study using data on residential apartments the method performed better than such techniques as CHAID, CART, KNN, multiple regression analysis, Artificial Neural Networks (MLP and RBF) and Boosted Trees. An approach for automatic detection of segments where a model significantly underperforms and for detecting segments with systematically under- or overestimated prediction is introduced. This segmentational approach is applicable to various expert systems including, but not limited to, those used for the mass appraisal.

• Item Type: MPRA Paper
• Language: English
• Keywords: Random forest, mass appraisal, CART, model diagnostics, real estate, automatic valuation model
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C45 - Neural Networks and Related Topics; L - Industrial Organization > L8 - Industry Studies: Services > L85 - Real Estate Services

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