False Negative - AI & ML Glossary | Farez Vadsaria

Model Evaluation & Metrics

False Negative

Positive cases that are incorrectly predicted as negative (Type II error) in classification.

This concept is essential for understanding model evaluation & metrics and forms a key part of modern AI systems.

Confusion Matrix
Recall
Type II Error

Tags

model-evaluation-metrics confusion-matrix recall type-ii-error

Related Terms

Confusion Matrix

A table showing true positives, true negatives, false positives, and false negatives for classification evaluation.

Recall

The proportion of true positives among all actual positives - measures how many actual positives were correctly identified.

← Back to All Terms