The F1 evaluation metric is more important in any case. F1 score sort maintains a balance between the precision and recall for the classifier. If the precision is low, the F1 is low and if the recall is low again F1 score is low. The F1 score is a number between 0 and 1 and is the harmonic mean of precision and recall.
F1 Score = 2*Precision x Recall/Precision + Recall
When we have a value of 1 (that is 100%) for both Precision and Recall, the F1 score would also be an ideal 1 (100%). It is known as the perfect value for F1 Score. As the values of both Precision and Recall range from 0 to 1, the F1 score also ranges from 0 to 1.
Study more about Evaluation at Evaluation Class 10