Question on labels in machine-learning Suppose that $X$ and $T$ are both random variables. Where $T$ is a label.
I just want to ask is tha finding probabilities on the label $P(T=t)$ or conditional probabilities $P(X=x|T=t)$ meaningful or necessary ?
Since, I never see an example that finding these probabilities yet and I am new to the term "label" here.
Thanks for answering !

They're neither unmeaningful nor unnecessary. For example, Bayes classifier (or Naive Bayes more commonly) explicitly uses them. $P(T=t)$ is the prior probability of the label, and $P(X=x|T=t)$ is the conditional likelihood of the sample.
