Hedonic price models and indices based on boosting applied to the Dutch housing market

We create a hedonic price model for house prices for six geographical submarkets in the Netherlands. Our model is based on a recent data mining technique called boosting. Boosting is an ensemble technique that combines multiple models, in our case decision trees, into a combined prediction. Boosting enables capturing of complex nonlinear relationships and interaction effects between input variables. We report mean relative errors and mean absolute error for all regions and compare our models with a standard linear regression approach. Our model improves prediction performance with up to 40% co... Mehr ...

Verfasser: Kagie, M. (Martijn)
Wezel, M.C. (Michiel) van
Dokumenttyp: workingPaper
Erscheinungsdatum: 2006
Schlagwörter: data mining / gradient boosting / hedonic price index / hedonic price models / housing / machine learning
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26677874
Datenquelle: BASE; Originalkatalog
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Link(s) : http://repub.eur.nl/pub/7665