4.8 Editorial Material

Avoiding common pitfalls in machine learning omic data science

Journal

NATURE MATERIALS
Volume 18, Issue 5, Pages 422-427

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41563-018-0241-z

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This Comment describes some of the common pitfalls encountered in deriving and validating predictive statistical models from high-dimensional data. It offers a fresh perspective on some key statistical issues, providing some guidelines to avoid pitfalls, and to help unfamiliar readers better assess the reliability and significance of their results.

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