Accuracy, precision, recall

1. What is the accuracy recall and precision?
2. Is accuracy and recall same?
3. What is accuracy precision and recall in machine learning?
4. Should I use precision or recall?

What is the accuracy recall and precision?

An alternative to using classification accuracy is to use precision and recall metrics. ... Precision quantifies the number of positive class predictions that actually belong to the positive class. Recall quantifies the number of positive class predictions made out of all positive examples in the dataset.

Is accuracy and recall same?

If we have to say something about it, then it indicates that sensitivity (a.k.a. recall, or TPR) is equal to specificity (a.k.a. selectivity, or TNR), and thus they are also equal to accuracy.

What is accuracy precision and recall in machine learning?

When it comes to precision we're talking about the true positives over the true positives plus the false positives. As opposed to recall which is the number of true positives over the true positives and the false negatives.

Should I use precision or recall?

Recall is more important than precision when the cost of acting is low, but the opportunity cost of passing up on a candidate is high.