Applying a CART-based approach for the diagnostics of mass appraisal models

Evgeny Antipov and Elena Pokryshevskaya

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper an approach for automatic detection of segments where a regression 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. The proposed approach may be useful for various regression analysis applications, especially those with strong heteroscedasticity. It helps to reveal segments for which separate models or appraiser assistance are desirable. The segmentational approach has been applied to a mass appraisal model based on the Random Forest algorithm.

Keywords: CART; model diagnostics; mass appraisal; real estate; Random forest; heteroscedasticity (search for similar items in EconPapers)
JEL-codes: C4 C45 L85 (search for similar items in EconPapers)
Date: 2010-12-01
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/27646/1/MPRA_paper_27646.pdf original version (application/pdf)

Related works:
Journal Article: Applying a CART-based approach for the diagnostics of mass appraisal models (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:27646

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().