Results for "area under ROC"

Scalar summary of ROC; measures ranking ability, not calibration.

Often more informative than ROC on imbalanced datasets; focuses on positive class performance.

Plots true positive rate vs false positive rate across thresholds; summarizes separability.

Learning where data arrives sequentially and the model updates continuously, often under changing distributions.

Neural networks can approximate any continuous function under certain conditions.

Formal framework for sequential decision-making under uncertainty.

What would have happened under different conditions.

Set of vectors closed under addition and scalar multiplication.

Vector whose direction remains unchanged under linear transformation.

Average value under a distribution.

Optimization under equality/inequality constraints.

Optimization under uncertainty.

Maintaining alignment under new conditions.

Privacy risk analysis under GDPR-like laws.

Control that remains stable under model uncertainty.

Motion of solid objects under forces.

Testing AI under actual clinical conditions.

Maximum expected loss under normal conditions.