Output Edge Cases

From The Foundation for Best Practices in Machine Learning

Output Edge Cases


Document and assess the causes, occurrence probabilities, overall performance impact of Edge Cases output by Model(s), inclusive of on Model training and design. If their influence is significant, improve model design. If occurrence is high, increase Model, code and data quality control.


To (a) assess and control for the impact of Output Edge Cases on Model design, bugs and performance; and (b) highlight associated risks that might occur in the Product Lifecycle.

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