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On the suitability of combining feature selection and resampling to manage data complexity
dc.contributor.author | Martín Félez, Raúl | |
dc.contributor.author | Mollineda, Ramón A. | |
dc.date.accessioned | 2012-01-03T08:59:37Z | |
dc.date.available | 2012-01-03T08:59:37Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Martín-Félez R., Mollineda R.A. (2010) On the Suitability of Combining Feature Selection and Resampling to Manage Data Complexity. In: Meseguer P., Mandow L., Gasca R.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2009. Lecture Notes in Computer Science, vol 5988. Springer | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://hdl.handle.net/10234/29990 | |
dc.description.abstract | The effectiveness of a learning task depends on data com- plexity (class overlap, class imbalance, irrelevant features, etc.). When more than one complexity factor appears, two or more preprocessing techniques should be applied. Nevertheless, no much effort has been de- voted to investigate the importance of the order in which they can be used. This paper focuses on the joint use of feature reduction and bal- ancing techniques, and studies which could be the application order that leads to the best classification results. This analysis was made on a spe- cific problem whose aim was to identify the melodic track given a MIDI file. Several experiments were performed from different imbalanced 38- dimensional training sets with many more accompaniment tracks than melodic tracks, and where features were aggregated without any correla- tion study. Results showed that the most effective combination was the ordered use of resampling and feature reduction techniques. | |
dc.format.extent | 10 p. | |
dc.language.iso | eng | |
dc.publisher | Springer Verlag | |
dc.relation.isFormatOf | Versió pre-print del document publicat a: http://www.springerlink.com/content/n36v1068r2325786/ | |
dc.relation.isPartOf | Lecture notes in computer science, vol. 5988 (2010) | |
dc.rights.uri | http://rightsstatements.org/vocab/CNE/1.0/ | * |
dc.subject | Data complexity | |
dc.subject | Feature reduction | |
dc.subject | Class imbalance problem | |
dc.subject | Melody finding | |
dc.subject | Music information retrieval | |
dc.subject.other | Intel·ligència artificial--Aplicacions a la música | |
dc.title | On the suitability of combining feature selection and resampling to manage data complexity | |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | https://doi.org/10.1007/978-3-642-14264-2_15 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
dc.relation.publisherVersion | https://link.springer.com/chapter/10.1007/978-3-642-14264-2_15 | |
dc.type.version | info:eu-repo/semantics/submittedVersion |
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