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...

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Detalles Bibliográficos
Autores principales: Kircher, Magdalena, Säurich, Josefin, Selle, Michael, Jung, Klaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9956321/
https://www.ncbi.nlm.nih.gov/pubmed/36833313
http://dx.doi.org/10.3390/genes14020387

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