Classification & Model Evaluation Calculators

Measure how well a test or classifier separates true cases from false ones.

5 calculators in this category.

A classifier or diagnostic test makes a yes-or-no prediction, and every prediction is either right or wrong in one of four ways: true positive, false positive, true negative, or false negative. The calculators here start from those four counts and derive the measures used to judge performance.

No single measure tells the whole story. Accuracy can look high on unbalanced data even when a model misses most of the rare cases, so it is worth reading several measures together.

Key concepts

Confusion matrix
A table of the four outcome counts. Every other measure in this category is calculated from it.
Sensitivity and specificity
Sensitivity is the share of actual positives correctly identified. Specificity is the share of actual negatives correctly identified.
Class imbalance
When one class is much rarer than the other, overall accuracy can be misleading.