Results for "true positive rate"

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

Adjusting learning rate over training to improve convergence.

Of predicted positives, the fraction that are truly positive; sensitive to false positives.

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

Of true positives, the fraction correctly identified; sensitive to false negatives.

Of true negatives, the fraction correctly identified.

The degree to which predicted probabilities match true frequencies (e.g., 0.8 means ~80% correct).

Measures divergence between true and predicted probability distributions.

Gradually increasing learning rate at training start to avoid divergence.

Probabilities do not reflect true correctness.

Maximum system processing rate.

Rate at which AI capabilities improve.

Controls the size of parameter updates; too high diverges, too low trains slowly or gets stuck.