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Impact of Label Noise on the Learning Based Models for a Binary Classification of Physiological Signal
Label noise is omnipresent in the annotations process and has an impact on supervised learning algorithms. This work focuses on the impact of label noise on the performance of learning models by examining the effect of random and class-dependent label noise on a binary classification task: quality a...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572105/ https://www.ncbi.nlm.nih.gov/pubmed/36236265 http://dx.doi.org/10.3390/s22197166 |