"weighted avg": {
"precision": 0.884810405643739,
"recall": 0.8888888888888888,
"f1-score": 0.8816091316091317,
"support": 108
}
What does support mean in above when we run rasa test?
"weighted avg": {
"precision": 0.884810405643739,
"recall": 0.8888888888888888,
"f1-score": 0.8816091316091317,
"support": 108
}
What does support mean in above when we run rasa test?
From the Scikit-Learn docs:
precision
is the ratio tp / (tp + fp)
where tp
is the number of true positives and fp
the number of false positives. The precision is intuitively the ability of the classifier not to label as positive a sample that is negative.
recall
is the ratio tp / (tp + fn)
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.
f1-score
is the harmonic mean of precision
and recall
.
support
is the number of occurrences of each class in y_true
.