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SVM-RFE: selection and visualization of the most relevant features through non-linear kernels
BACKGROUND: Support vector machines (SVM) are a powerful tool to analyze data with a number of predictors approximately equal or larger than the number of observations. However, originally, application of SVM to analyze biomedical data was limited because SVM was not designed to evaluate importance...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6245920/ https://www.ncbi.nlm.nih.gov/pubmed/30453885 http://dx.doi.org/10.1186/s12859-018-2451-4 |