Mastering Python for Finance - Second Edition

Recall score

The recall score is the ratio of correctly predicted positive observations to all the observations in the actual class, and can be written as follows:

This gives a recall score of between 0 and 1, with 1 as the best value. The recall_score function of the sklearn.metrics module calculates this score for us with the following code:

In [ ]:    from sklearn.metrics import recall_score    print('recall_score:', recall_score(actual, predicted))Out[ ]:    recall_score: 0.56

The recall score suggests that our logistic regression model correctly identifies positive samples 56% of the time.