Comparative Analysis of Regression Tree Models for Premises Valuation Using Statistica Data Miner

Authors:
Tadeusz Lasota;Piotr Sachnowski;Bogdan Trawiński
Affiliations:
Dept. of Spatial Management, Wrocław University of Environmental and Life Sciences, Wroclaw, Poland 50-375;Institute of Informatics, Wrocław University of Technology, Wrocław, Poland 50-370;Institute of Informatics, Wrocław University of Technology, Wrocław, Poland 50-370
Venue:
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Year:
2009

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Abstract

Several dozen of experiments were conducted with Statistica Data Miner in order to assess the suitability of different machine learning algorithms for an Internet expert system to assist with real estate appraisal. The investigations concentrated first of all on regression trees and ensemble tree models. Moreover, decision tree approaches were compared with commonly used algorithms as KNN, SVM and a multilayer perceptron neural network. The results provided by the collection of twelve predictive accuracy measures were also analyzed. The study proved the usefulness of majority of algorithms to build the real estate valuation models.