In classification tasks, we can interpret the output vector as how "confident" the model is that the input has a certain label. For example,
y = [0.01 0.20 0.99 0.10]
would mean the model is 99% certain the input has label with index 2 and 1% certain it has label with index 0.
My question is: Is there an equivalent for regression tasks?
If my output looks like
y = 0.33
is there a way to measure how "certain" the model is that the output really is 0.33?