Mazza, Sabina (2014) Advances in the combination of supervised classification Methods: an experimental study. Working Paper. MEMOTEF, Roma.
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Abstract
In this work we were interested in investigating the predictive accuracy of one of the most popular learning schemes for the combination of supervised classification methods: the Stacking Technique proposed by Wolpert (1992) and consolidated by Ting and Witten, (1999) and Seewald (2002). In particular, we made reference to the StackingC (Seewald 2002) as a starting point for our analysis, to which some modifications and extensions were made. Since most of the research on ensembles of classifiers tends to demonstrate that this scheme can perform comparably to the best of the base classifiers as selected by cross-validation, if not better, this motivated us to investigate the performance of the Stacking empirically. An analysis of the results obtained by applying the our Stacking scheme, which includes differences and characteristic implementations compared to what is proposed by the literature, to the set of the dataset generated by means of an experimental design does not lead us to believe that the Stacking scheme is preferable in terms of performances to the use of the best single classifier. It always achieves good performances and is to be considered among the best. On the contrary, in the case of contaminated data, Stacking improves its performances noticeably, and generally appears to be very competitive, above all when the contaminations are more substantial.
| Item Type: | Monograph (Working Paper) |
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| Additional Information: | Fa parte di Working paper n.133 October 2014, ISSN: 1568-4555 |
| Uncontrolled Keywords: | Supervised classification methods, Ensemble learning, Stacking, Meta-level learning, Cross-validation |
| Subjects: | 300 Scienze sociali 500 Scienze naturali e Matematica > 510 Matematica > 519 Probabilità e Matematica applicata > 519.5 Statistica matematica (Classificare qui i metodi parametrici e non parametrici) |
| Depositing User: | Dr. Sabina Mazza |
| Date Deposited: | 13 Oct 2014 13:10 |
| Last Modified: | 20 Feb 2015 10:24 |
| URI: | http://eprints.bice.rm.cnr.it/id/eprint/10032 |
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