'Why does Jaccard similarity score is the same as accuarcy score in binary classification?
In sklearn document (https://scikit-learn.org/0.15/modules/generated/sklearn.metrics.jaccard_similarity_score.html), it said:
In binary and multiclass classification, this function is equivalent to the accuracy_score. It differs in the multilabel classification problem.
However, according to the Jaccard index on Wikipedia (https://en.wikipedia.org/wiki/Jaccard_index)
It clearly differs from the accuracy score ((TP+TN)/(TP+FP+FN+TN)).
Might someone explain me that's which is correct, and why?
Solution 1:[1]
The 0.15 documentation is outdated, check the stable version that no longer points out metrics.jaccard_score is the same as accuracy for binary classification.
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | jcaliz |

