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nbokulich avatar nbokulich commented on June 25, 2024

Hi @hh1985, thanks for asking! I removed these metrics because they were not particularly useful and were very prone to disturbance in compositional data. Overall, other quantitative metrics such as F-measure are much more informative.

These should still be somewhere in the version history if they are needed.

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hh1985 avatar hh1985 commented on June 25, 2024

Hi @nbokulich , thanks for the information! If Pearson/Spearman correlation is not recommended, what should I use to evaluate the quantification performance of a method?

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nbokulich avatar nbokulich commented on June 25, 2024

Hi @hh1985 I would recommend the precision/recall/F-measure metrics. Check out the ipython notebooks (any with "evaluation" in the name) to see how to use these on taxonomy classification data in tax-credit.

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hh1985 avatar hh1985 commented on June 25, 2024

@nbokulich Thanks a lot!

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