Does anybody know any regression/prediction/supervised learning method if I have arbitrary independent and dependent variables with Intervals?
For example, I have an observation with epistemic uncertainty that modeled as interval such as:
| x_1 | x_2 | y |
|---|---|---|
| [1,3] | [3,4] | [-1,0] |
| [-2,0] | [1,4] | [4,5.5] |
| [2,3] | [6,8] | [5,8] |
| ... | ... | ... |
How can I model this kind of data with regression technique?
I found some solutions mentioned interval censored data. But I guess, that's not the case. I also found some others, but they seem to only allow the uncertainty propagation from the independent variable to the dependent variables. Meanwhile, in my case, I think I need to include the interval dependent variable into the fitting/training process.
Does anybody knows any reference for this problem?