LOCALLY REGULARIZED LINEAR REGRESSION IN THE VALUATION OF REAL ESTATE

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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics , Statistics & Probability

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ISSN: 1234-7655
eISSN: 2450-0291

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VOLUME 17 , ISSUE 3 (September 2016) > List of articles

LOCALLY REGULARIZED LINEAR REGRESSION IN THE VALUATION OF REAL ESTATE

Mariusz Kubus *

Keywords : large transactional data, local regression, feature selection, regularization, cross-validation

Citation Information : Statistics in Transition New Series. Volume 17, Issue 3, Pages 515-524, DOI: https://doi.org/10.21307/stattrans-2016-035

License : (CC BY 4.0)

Published Online: 06-July-2017

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ABSTRACT

Regression methods are used for the valuation of real estate in the comparative approach. The basis for the valuation is a data set of similar properties, for which sales transactions were concluded within a short period of time. Large and standardized databases, which meet the requirements of the Polish Financial Supervision Authority, are created in Poland and used by the banks involved in mortgage lending, for example. We assume that in the case of large data sets of transactions, it is more advantageous to build local regression models than a global model. Additionally, we propose a local feature selection via regularization. The empirical research carried out on three data sets from real estate market confirmed the effectiveness of this approach. We paid special attention to the model quality assessment using cross-validation for estimation of the residual standard error.

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