Paper Info
Title
Analysis of bagging ensembles of fuzzy models for premises valuation
Abstract
The investigation of 16 fuzzy algorithms implemented in data mining system KEEL from the point of view of their usefulness to create bagging ensemble models to assist with real estate appraisal were presented in the paper. All the experiments were conducted with a real-world dataset derived from a cadastral system and registry of real estate transactions. The results showed there were significant differences in accuracy between individual algorithms. The analysis of measures of error diversity revealed that only the highest values of an average pairwise correlation of outputs were a profitable criterion for the selection of ensemble members.
Year
DOI
Venue
2010
10.1007/978-3-642-12101-2_34
ACIIDS
Keywords
Field
DocType
fuzzy model,bagging ensemble model,fuzzy algorithm,average pairwise correlation,error diversity,data mining system keel,real estate appraisal,cadastral system,premises valuation,real estate transaction,ensemble member,highest value,real estate,data mining,profitability
Pairwise comparison,Data mining,Real estate,Real estate appraisal,Ensemble forecasting,Cadastre,Computer science,Fuzzy logic,Artificial intelligence,Valuation (finance),Machine learning,Genetic fuzzy systems
Conference
Volume
ISSN
ISBN
5991
0302-9743
3-642-12100-5
Citations 
PageRank 
References 
13
0.57
28
Authors
4
Name
Order
Citations
PageRank
Marek Krzystanek1161.02
Tadeusz Lasota234825.33
Zbigniew Telec317014.92
Bogdan Trawiński428824.72