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Peering Into the Black Box of Artificial Intelligence: Evaluation Metrics of Machine Learning Methods
402
Zitationen
8
Autoren
2018
Jahr
Abstract
Attention to sample size, overfitting, underfitting, cross validation, as well as a broad knowledge of the metrics of machine learning, can help those with little or no technical knowledge begin to assess machine learning studies. However, transparency in methods and sharing of algorithms is vital to allow clinicians to assess these tools themselves.
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