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.
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Lasota, T., Sachnowski, P., Trawiński, B. (2009). Comparative Analysis of Regression Tree Models for Premises Valuation Using Statistica Data Miner. In: Nguyen, N.T., Kowalczyk, R., Chen, SM. (eds) Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems. ICCCI 2009. Lecture Notes in Computer Science(), vol 5796. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04441-0_68
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DOI: https://doi.org/10.1007/978-3-642-04441-0_68
Publisher Name: Springer, Berlin, Heidelberg
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