Toward a General-Purpose Heterogeneous Ensemble for Pattern Classification

We perform an extensive study of the performance of different classification approaches on twenty-five datasets (fourteen image datasets and eleven UCI data mining datasets). The aim is to find General-Purpose (GP) heterogeneous ensembles (requiring little to no parameter tuning) that perform compet...

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Detalles Bibliográficos
Autores principales: Nanni, Loris, Brahnam, Sheryl, Ghidoni, Stefano, Lumini, Alessandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564633/
https://www.ncbi.nlm.nih.gov/pubmed/26413089
http://dx.doi.org/10.1155/2015/909123

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564633/
https://www.ncbi.nlm.nih.gov/pubmed/26413089
http://dx.doi.org/10.1155/2015/909123

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