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Assessing Outlier Probabilities in Transcriptomics Data When Evaluating a Classifier
Outliers in the training or test set used to fit and evaluate a classifier on transcriptomics data can considerably change the estimated performance of the model. Hence, an either too weak or a too optimistic accuracy is then reported and the estimated model performance cannot be reproduced on indep...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9956321/ https://www.ncbi.nlm.nih.gov/pubmed/36833313 http://dx.doi.org/10.3390/genes14020387 |