What is the Jaccard Index?
- Jaccard Coefficient
- Jaccard’s Coefficient of Community
- Jaccard Similarity Coefficient
- Jaccard–Tanimoto Coefficient
- Tanimoto Similarity Coefficient
- Short’s Measure
- Intersection over Union (see image)
The Jaccard Index can be calculated as follows:
In general, the JI is a proper tool for assessing the similarity and diversity of data sets. Within the context of evaluating a classifier, the JI can be interpreted as a measure of overlap between the ground truth and estimated classes, with a focus on true positives and ignoring true negatives.
Consequently, the JI suffers from the same criticism as the F-Measure: It exclusively focuses on the positive class and ignores the true negatives (TN). That’s why it is not the best performance metric in situations of class imbalance.