A pitfall for machine learning methods aiming to predict across cell types

A pitfall for machine learning methods aiming to predict across cell types

Abstract Machine learning models that predict genomic activity are most useful when they make accurate predictions across cell types. Here, we show that when the training and test sets contain the same genomic loci, the resulting model may falsely appear to perform well by effectively memorizing the...

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Bibliographic Details
Main Authors: Jacob Schreiber, Ritambhara Singh, Jeffrey Bilmes, William Stafford Noble
Format: Article
Language:English
Published: BMC 2020-11-01
Series:Genome Biology
Subjects:
Machine learning
Epigenomics
Genomics
Online Access:http://link.springer.com/article/10.1186/s13059-020-02177-y

Internet

http://link.springer.com/article/10.1186/s13059-020-02177-y

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