Machine Learning
Computers and Operations Research
An empirical comparison of supervised learning algorithms
ICML '06 Proceedings of the 23rd international conference on Machine learning
Random Forests for multiclass classification: Random MultiNomial Logit
Expert Systems with Applications: An International Journal
Determinants of house prices in Turkey: Hedonic regression versus artificial neural network
Expert Systems with Applications: An International Journal
The mass appraisal of the real estate by computational intelligence
Applied Soft Computing
Application of fuzzy neural network for real estate prediction
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
A novel approach to estimate proximity in a random forest: An exploratory study
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
To the best knowledge of authors, the use of Random forest as a potential technique for residential estate mass appraisal has been attempted for the first time. In the empirical study using data on residential apartments the method performed better than such techniques as CHAID, CART, KNN, multiple regression analysis, Artificial Neural Networks (MLP and RBF) and Boosted Trees. An approach for automatic detection of segments where a model significantly underperforms and for detecting segments with systematically under- or overestimated prediction is introduced. This segmentational approach is applicable to various expert systems including, but not limited to, those used for the mass appraisal.