I have a dataset of people who all have undergone a dietary intervention. Not all participants gave both samples, so I excluded them and only kept those for which I have Visit1 and Visit7, leaving a decent n=54 for both groups. And of course expecting predictions better than the 50% luck threshold.
But I get the opposite!
I have tried all that came in in mind, like trying the other algorithms, setting other parameters (ex. seed, etc.). I have ran it on the L6_table (collapsed at genus level) and got this, but also did with the ASV table. Very similar results.
I join a .zip of my working tables and (simplified) metadata + taxonomy (ant the .txt table for verifications…) if you some people want to try for themselves.
BugReport-ML_NegativeLearning.zip (2.3 MB)
Thanks in advance,
Best regards, -JA