8.16.1.5. sklearn.metrics.recall_score¶
- sklearn.metrics.recall_score(y_true, y_pred, pos_label=1)¶
Compute the recall
The recall is the ratio where tp is the number of true positives and fn the number of false negatives. The recall is intuitively the ability of the classifier to find all the positive samples.
The best value is 1 and the worst value is 0.
Parameters : y_true : array, shape = [n_samples]
true targets
y_pred : array, shape = [n_samples]
predicted targets
pos_label : int
in the binary classification case, give the label of the positive class (default is 1). Everything else but ‘pos_label’ is considered to belong to the negative class. Not used in the case of multiclass classification.
Returns : recall : float
recall of the positive class in binary classification or weighted avergage of the recall of each class for the multiclass task.