Name
Title | ||
|---|---|---|
Comparison of bagging, boosting and stacking ensembles applied to real estate appraisal |
Abstract | ||
|---|---|---|
The experiments, aimed to compare three methods to create ensemble models implemented in a popular data mining system called WEKA, were carried out. Six common algorithms comprising two neural network algorithms, two decision trees for regression, linear regression, and support vector machine were used to construct ensemble models. All algorithms were employed to real-world datasets derived from the cadastral system and the registry of real estate transactions. Nonparametric Wilcoxon signed-rank tests to evaluate the differences between ensembles and original models were conducted. The results obtained show there is no single algorithm which produces the best ensembles and it is worth to seek an optimal hybrid multi-model solution. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-12101-2_35 | ACIIDS |
Keywords | Field | DocType |
best ensemble,optimal hybrid multi-model solution,nonparametric wilcoxon signed-rank test,real estate appraisal,linear regression,decision tree,common algorithm,cadastral system,neural network algorithm,ensemble model,popular data mining system,bagging,data mining,real estate,ensemble models,stacking,support vector machine,neural network,boosting | Data mining,Decision tree,Ensemble forecasting,Computer science,Support vector machine,Wilcoxon signed-rank test,Nonparametric statistics,Artificial intelligence,Boosting (machine learning),Artificial neural network,Machine learning,Linear regression | Conference |
Volume | ISSN | ISBN |
5991 | 0302-9743 | 3-642-12100-5 |
Citations | PageRank | References |
17 | 0.69 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Magdalena Graczyk | 1 | 54 | 3.39 |
| Tadeusz Lasota | 2 | 348 | 25.33 |
| Bogdan Trawiński | 3 | 288 | 24.72 |
| Krzysztof Trawiński | 4 | 247 | 16.06 |