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Improving data splitting for classification applications in spectrochemical analyses employing a random-mutation Kennard-Stone algorithm approach
MOTIVATION: Data splitting is a fundamental step for building classification models with spectral data, especially in biomedical applications. This approach is performed following pre-processing and prior to model construction, and consists of dividing the samples into at least training and test set...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954661/ https://www.ncbi.nlm.nih.gov/pubmed/31116391 http://dx.doi.org/10.1093/bioinformatics/btz421 |