Articles | Volume 45
https://doi.org/10.5194/adgeo-45-377-2018
https://doi.org/10.5194/adgeo-45-377-2018
29 Nov 2018
 | 29 Nov 2018

Accuracy measurement of Random Forests and Linear Regression for mass appraisal models that estimate the prices of residential apartments in Nicosia, Cyprus

Thomas Dimopoulos, Hristos Tyralis, Nikolaos P. Bakas, and Diofantos Hadjimitsis

Viewed

Total article views: 3,469 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,955 421 93 3,469 183 65 48
  • HTML: 2,955
  • PDF: 421
  • XML: 93
  • Total: 3,469
  • Supplement: 183
  • BibTeX: 65
  • EndNote: 48
Views and downloads (calculated since 29 Nov 2018)
Cumulative views and downloads (calculated since 29 Nov 2018)

Viewed (geographical distribution)

Total article views: 3,117 (including HTML, PDF, and XML) Thereof 3,057 with geography defined and 60 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 May 2024
Download

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
The paper examines a machine learning algorithm (Random Forests) in comparison with Multivariate Linear Regression, for a data-set of 3500 transactions of residential apartments in Nicosia District in Cyprus. The methodology suggested, indicated high accuracy of the Random Forests Method, that can be applied in automated valuation models and CAMA systems.