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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees, Wadsworth Int. Group, Belmont (1984)
Torgo, L.: Functional Models for Regression Tree Leaves. In: Proc. 14th International Conference on Machine Learning, pp. 385–393. Morgan Kaufmann, San Francisco (1997)
Badulescu, L.A., Nicula, A.: Data Mining Decision Trees in Economy. Analele Universitatii din Oradea, Stiinte Economice XVI II, 723–727 (2007)
Giudici, P., Figini, S.: Applied Data Mining for Business and Industry. Wiley, Chichester (2009)
Trana, V.T., Yanga, B.S., Oha, M.S., Tanb, A.C.C.: Machine condition prognosis based on regression trees and one-step-ahead prediction, Mech. Systems and Signal Process. 22(5), 1179–1193 (2008)
Khoshgoftaar, T.M., Seliya, N.: Tree-based software quality estimation models for fault prediction. In: Proc. 8th IEEE Symp. on Software Metrics, pp. 203–214 (2002)
Wang, X., Dietterich, T.G.: Efficient Value Function Approximation Using Regression Trees. In: Proceedings of the IJCAI Workshop on Statistical Machine Learning for Large-Scale Optimization (1999)
Podgorelec, V., Kokol, P., Stiglic, B., Rozman, I.: Decision trees: an overview and their use in medicine. Journal of Medical Systems 26, 445–463 (2002)
Balac, N., Gaines, D.M., Fisher, D.: Using Regression Trees to Learn Action Models. IEEE Int. Conference on Man and Cybernetics 5, 3378–3383 (2000)
Acciani, C., Fucilli, V., Sardaro, R.: Model Tree: An Application in Real Estate Appraisal, 109th EAAE Seminar, no. 44853, Viterbo (2008)
Gokhale, S.S., Lyu, M.R.: Regression tree modeling for the prediction of software quality. In: Proc. of ISSAT 1997, pp. 31–36 (1997)
Perlich, C., Provost, F., Simonoff, J.S.: Tree induction vs. logistic regression: a learning-curve analysis. J. of Machine Learning Res. 4, 211–255 (2003)
Quinlan, J.R.: Learning with Continuous Classes. In: 5th Australian Joint Conference on Artificial Intelligence (AI 1992), Singapore, pp. 343–348 (1992)
Król, D., Lasota, T., Trawiński, B., Trawiński, K.: Investigation of evolutionary optimization methods of TSK fuzzy model for real estate appraisal. International Journal of Hybrid Intelligent Systems 5(3), 111–128 (2008)
Lasota, T., Pronobis, E., Trawiński, B., Trawiński, K.: Exploration of Soft Computing Models for the Valuation of Residential Premises using the KEEL Tool. In: Nguyen, N.T., et al. (eds.) 1st Asian Conference on Intelligent Information and Database Systems (ACIIDS 2009), pp. 253–258. IEEE, Los Alamitos (2009)
Hill, T., Lewicki, P.: Statistics: Methods and Applications. StatSoft, Tulsa (2007)
Breiman, L.: Random Forests. Machine Learning 45, 5–32 (2001)
Hagquist, C., Stenbeck, M.: Goodness of Fit in Regression Analysis – R2 and G2 Reconsidered. Quality & Quantity 32, 229–245 (1998)
Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-642-04441-0_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04440-3
Online ISBN: 978-3-642-04441-0
eBook Packages: Computer ScienceComputer Science (R0)