Catastrophic Failures

From The Foundation for Best Practices in Machine Learning

Catastrophic Failures


Document and assess the prevalence of predictions with High Confidence Values, but large Evaluation Errors. If apparent, improve Model to avoid these, and/or implement processes to mitigate these as much as is reasonably practical.


To (a) assess the propensity of the Model for catastrophic failures; and (b) highlight associated risks that might occur in the Product Lifecycle.

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