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Detecting representative data and generating synthetic samples to improve learning accuracy with imbalanced data sets
It is difficult for learning models to achieve high classification performances with imbalanced data sets, because with imbalanced data sets, when one of the classes is much larger than the others, most machine learning and data mining classifiers are overly influenced by the larger classes and igno...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542532/ https://www.ncbi.nlm.nih.gov/pubmed/28771522 http://dx.doi.org/10.1371/journal.pone.0181853 |