The strategy used to aggregate per-class precision/recall/F-score into a
single number when there are more than two classes (or no positiveLabel
is configured).
"macro": unweighted mean across classes.
"micro": pool true/false positives and false negatives across classes
before computing the metric.
"weighted": mean across classes, weighted by each class's support
(number of true instances).
The strategy used to aggregate per-class precision/recall/F-score into a single number when there are more than two classes (or no
positiveLabelis configured)."macro": unweighted mean across classes."micro": pool true/false positives and false negatives across classes before computing the metric."weighted": mean across classes, weighted by each class's support (number of true instances).