AI engineering glossary · Evaluation metrics
What is jaccard index?
Jaccard index (also called intersection over union, Jaccard similarity): A measure of overlap between two sets: the size of their intersection divided by the size of their union. Applied to classification it equals TP / (TP + FP + FN), ignoring true negatives. It runs from 0 (no overlap) to 1 (identical sets).
Jaccard index: an example
A model predicts tags {python, sql, git} and the true tags are {python, sql, docker}. The intersection has 2 items and the union 4, so the Jaccard index is 0.5.
Related terms
More Evaluation metrics terms
- Kendall's tau
- Kolmogorov-Smirnov statistic
- Krippendorff's alpha
- Likelihood ratio
- Log loss
- Macro averaging
- Matthews correlation coefficient
- MAUVE
Where you learn it
Jaccard index is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.