How to interpret the classification report of scikit-learn?

145    Asked by DavidEDWARDS in Data Science , Asked on Feb 15, 2023

As you can see, it is about a binary classification with linearSVC. The class 1 has a higher precision than class 0 (+7%), but class 0 has a higher recall than class 1 (+11%). How would you interpret this?


And two other questions: what does "support" stand for? The precision and recall scores in the classification report are different compared to the results of sklearn.metrics.precision_score or recall_score. Why is that so?

Answered by Ranjana Admin

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