Explain what precision and recall are?
- Precision : Precision is the ratio of correctly predicted positive observations of the total predicted positive observations.
Precision = (TP/TP+FP)
- Recall : Recall is the ratio of correctly predicted positive observations to all observations in the actual class
Recall = TP/TP+FN