Turn a Confusion Matrix Into Fixes

The largest confusion cell is refund_status predicted as refund_request and refund_request predicted as refund_status. Count confusion -> inspect examples -> classify cause -> choose targeted fix The common shortcut is to collect more examples for both labels without checking whether the label definitions are inconsistent. Find the off-diagonal Locate the largest mistaken label pair in the confusion matrix. Aggregate metrics hide the pairwise failure you need to fix. Sample the texts Read 20 to 60 examples from that cell and mark why each was hard. The cause may be label noise, rare phrasing, overlap, or threshold. Choose the fix Map…

Sign up free — one personalized lesson every day, matched to your role and goals.

Already have an account? Sign in