# How do I interpret the given classification report?

The given classification report was obtained from running a Random Forest binary classifier on the test data. There is huge class imbalance in the training data. How do I interpret the given classification report showing very high values for one particular label?

            precision    recall  f1-score   support

0       0.98      1.00      0.99     35050
1       0.98      0.72      0.83      1982
total       0.98      0.98      0.98     37032


F1-Score is a kind of average of the two; it's an attempt to provide a unified figure of the model's performance, but personally I consider it less useful than the separate figures. It's calculated via the formula 2 x ((precision x recall) / (precision + recall)).