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

Evgeny Antipov and Elena Pokryshevskaya

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Random forest; mass appraisal; CART; model diagnostics; real estate; automatic valuation model (search for similar items in EconPapers)
JEL-codes: C14 C45 L85 (search for similar items in EconPapers)
Date: 2010-07-29
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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