Go to content
UR Home

Interpretable machine learning for real estate market analysis

URN to cite this document:
DOI to cite this document:
Lorenz, Felix ; Willwersch, Jonas ; Cajias, Marcelo ; Fuerst, Franz
Date of publication of this fulltext: 18 Apr 2023 04:45

This publication is part of the DEAL contract with Wiley.


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 ...


Owner only: item control page
  1. Homepage UR

University Library

Publication Server


Publishing: oa@ur.de
0941 943 -4239 or -69394

Dissertations: dissertationen@ur.de
0941 943 -3904

Research data: datahub@ur.de
0941 943 -5707

Contact persons