AWS sagemaker documentation change
Summary
Corrected description of false negative in recall metric explanation (changed 'false positive' to 'false negative')
Security assessment
This change fixes a documentation error in metric definitions but does not relate to security features or vulnerabilities. The correction improves accuracy of machine learning concept explanations without security implications.
Diff
diff --git a/sagemaker/latest/dg/autopilot-metrics-validation.md b/sagemaker/latest/dg/autopilot-metrics-validation.md index 7a175bffd..e58c6f905 100644 --- a//sagemaker/latest/dg/autopilot-metrics-validation.md +++ b//sagemaker/latest/dg/autopilot-metrics-validation.md @@ -96 +96 @@ Recall measures how well an algorithm correctly predicts all of the true positiv -Recall is important when testing for cancer because it's used to find all of the true positives. A false positive (FP) reflects a positive prediction that is actually negative in the data. It is often insufficient to measure only recall, because predicting every output as a true positive yields a perfect recall score. +Recall is important when testing for cancer because it's used to find all of the true positives. A false negative (FN) reflects a negative prediction that is actually positive in the data. It is often insufficient to measure only recall, because predicting every output as a true positive yields a perfect recall score.