The Strength of Weak Learnability
Machine Learning
Machine Learning
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
A Theoretical Analysis of Bagging as a Linear Combination of Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Investigation of evolutionary optimization methods of TSK fuzzy model for real estate appraisal
International Journal of Hybrid Intelligent Systems - Recent Advances in Intelligent Paradigms Fusion and Their Applications
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Comparative Analysis of Premises Valuation Models Using KEEL, RapidMiner, and WEKA
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Comparison of data driven models for the valuation of residential premises using KEEL
International Journal of Hybrid Intelligent Systems - Hybrid Fuzzy Models
International Journal of Hybrid Intelligent Systems - Hybrid Fuzzy Models
Information Sciences: an International Journal
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Analysis of bagging ensembles of fuzzy models for premises valuation
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Comparison of bagging, boosting and stacking ensembles applied to real estate appraisal
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
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The experiments, aimed to compare the performance of bagging ensembles using three different test sets composed of base, out-of-bag, and 30% holdout instances were conducted. Six weak learners including conjunctive rules, decision stump, decision table, pruned model trees, rule model trees, and multilayer perceptron, implemented in the data mining system WEKA, were applied. All algorithms were employed to real-world datasets derived from the cadastral system and the registry of real estate transactions, and cleansed by property valuation experts. The analysis of the results was performed using recently proposed statistical methodology including nonparametric tests followed by post-hoc procedures designed especially for multiple n×n comparisons. The results showed the lowest prediction error with base test set only in the case of model trees and a neural network.