If the overall distribution of the outcome is heavily tilted towards one class compared to the other, the classification problem is considered to be imbalanced.
The specificity is the analog of recall for the negative class.
The F1 Score is the harmonic mean between precision and recall.
Recall measures the proportion of actual observations that belong to the positive class that were correctly classified
One of the most useful tools for evaluating the performance of any classification algorithm is the confusion matrix.