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F-score results for Cross Validation on Multi-target data
Hi Meka development team,
I have tried to evaluate a model for a multi-target dataset and would like to get the F-score result for individual target outputs with cross validation. Using Meka, it gives the accuracy but no F-score (Precision, Recall). Is there any way that I can produce the metric for this evaluation? I tried with Python's Sci-kit library but it doesn't support for multi-target data as well. Thanks in advance.
F1 is not implemented for multi-target (I don't do multi-label/-target, so not sure whether it is even possible in general).
Here are the implementations:
- multi-label stats get generated by MLEvalUtils.getMLStats
- multi-target stats get generated by MLEvalUtils.getMTStats