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Note: Training data here is limited (~13,000 issues both closed and opened), after the data cleaning process we expect this value to be greatly further reduced. Also, we have to consider that not all issues have been labelled and if labelled not all labels which may represent that issue have been 

Metrics:

Multi-label Classification:
Accurate prediction of at least one label in an issue across issues: ~87%
Accuracy in predicting all labels in an issue (i.e. an exact match of all labels to an issue) across issues: ~20%

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