When we care more that there should be no false negatives, as far as possible… ie. higher precision (video is suitable for kid or not), we should use (receiver operating characteristic) ROC (area under the curve) AUC
Scikit-Learn provides a function to compute this directly:
from sklearn.metrics import roc_auc_score
roc_auc_score(y_train_5, y_scores)
Similarly, when we care more about the false positives than the false negatives, example shop lifting case then what should we do?
Is there a direct function in scikit learn to calculate this?