- If it's 1 it means all positives are correct
- It may be that many other positives for this class are wrongly labelled as negative (and categorised in other classes), but that's not measured in this metric
- The lower it is, it means more entries from other categories are being mis-classified here
- If it's 1 it means it managed to find all the positive samples
- It may be that it wrongly classified other samples for other categories here, but that's not measured in this metric
- The lower it is, it means more entries from this category are being mis-classified into other categories
Support: Number of occurrence in each category
Reference: http://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_fscore_support.html
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