This CMU Machine Learning Text Book gives this formula to apply Bayes' rule
where $y_j$ denotes the jth possible value for Y, $x_k$ denotes the kth possible vector value for X.
I guess all of the kth possible vector value constitute the sample space. is my understanding right?
my concern is whether the term sample space in Machine Learning and the on in probability theory are the same?
it seems that Machine Learning articles rarely use the term sample space.