Live Data Quality

From The Foundation for Best Practices in Machine Learning

Live Data Quality

Control

Document and assess whether live incoming data with low quality (low-confidence, uncertain, nonsensical, missing and/or imputed attributes) can be handled appropriately by the Model on the per-Data Subject level. If not, implement additional measures, and/or re-assess validity of Product Definition(s) in view of non-applicability to low quality live subsets.


Aim

To (a) assess and control that all Product Subjects can be supported appropriately by the live Product; and (b) highlight associated risks that might occur in the Product Lifecycle.


Additional Information