Interpretable machine learning for real estate market analysis

URN to cite this document:: urn:nbn:de:bvb:355-epub-540745
DOI to cite this document:: 10.5283/epub.54074

Lorenz, Felix

; Willwersch, Jonas

; Cajias, Marcelo

; Fuerst, Franz

License: Creative Commons Attribution Non-commercial No Derivatives 4.0
PDF - Published Version
Early View
(2MB)

Date of publication of this fulltext: 18 Apr 2023 04:45

Alternative links to fulltext:DOI Publisher

This publication is part of the DEAL contract with Wiley.

Details

Preview: Early View

Export bibliographical data

Abstract

Machine Learning (ML) excels at most predictive tasks but its complex nonparametric structure renders it less useful for inference and out-of sample predictions. This article aims to elucidate and enhance the analytical capabilities of ML in real estate through Interpretable ML (IML). Specifically, we compare a hedonic ML approach to a set of model-agnostic interpretation methods. Our results ...