Hi Sam!



 shartzog:

I’m working on a multilabel classification problem.  I have four potential labels: “Hospitalized”, “Intubated”, “Deceased”, and “Pneumonia”.
…

Is adding in the 5th “None” label prior to training the right way forward?



You do not need (or want) a “None” label.  The “None” case is indicated
by none of your four given labels being active.
You have a multi-label, multi-class classification problem.  It is
multi-class because you have four classes, “Hospitalized,” “Intubated,”
“Deceased,” and “Pneumonia.”  It is multi-label because any number,
including all and none, of the labels can be active for any sample.
You say your model trains well.  I’m assuming that it trains well for
all label combinations, including no active labels (and, hopefully, you
have some no-active-label samples in your training data).  Provided
that this is the case, your model is fine, and, if you have an issue with
the “None” case in your post-training analysis, you need to fix it there,
rather than trying to tweak your model to sweep the issue under the rug.
Best.
K. Frank