Acceptance Criteria - Error Rate Analysis

From The Foundation for Best Practices in Machine Learning
Technical Best Practice Guideline > Model Decision-Making > Acceptance Criteria - Error Rate Analysis

Acceptance Criteria - Error Rate Analysis

Control

Consider the Societal and Industry Contexts in determining the acceptable method for error measurement, as discussed in Section 4 - Problem Mapping. Document and define the acceptable error types and rates for the Product as required by Representativeness & Specification, as discussed more thoroughly and technically in Section 13 - Representativeness & Specification. Analyze any potential tension between achievable and acceptable error rates and determine whether that tension can be resolved.


Aim

To (a) ensure appropriate error type and rate metrics for Model(s); and (b) highlight associated risks that might occur in the Product Lifecycle.


Additional Information