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Beyond accuracy: Measures for assessing machine learning ... | ResearchHub
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Beyond accuracy: Measures for assessing machine learning models, pitfalls and guidelines
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Authors
Richard Dinga
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Richard Dinga
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Brenda Penninx
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•
André Marquand
Published
August 22, 2019
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Preprint Server
Topics
Biology
Machine Learning
Computer Science
Mathematics
Physics
Show all topics
DOI
10.1101/743138
License
CC-BY-NC
Other Formats
PDF
Supporters
Support the authors with ResearchCoin
Tip RSC
Preprint Server
Topics
Biology
Machine Learning
Computer Science
Mathematics
Physics
Show all topics
DOI
10.1101/743138
License
CC-BY-NC
Other Formats
PDF
