# Supervised learning with error-range in labels?

I am working in a problem where labels have an error range (we know the range). For instance, a label can be expressed as $$y_i \pm e_i$$ with $$e_i$$ is the error range for the label of the instance $$i^{th}$$.

There are two problems with that:

1. Regression: If I want to infer the real value of $$y$$, how should I integrate the knowledge of error range into a regression model, say linear regression?

2. Classification: If I want to convert the problem to a classification problem by grouping similar $$y$$ values to a class (e.g. group age 11-19, 20-29, etc.) and I have a person with $$age = 20 \pm 2$$ (well, it is stupid, but just assume that we don't know for sure the age of a person), what class I should assume for this person?

I stuck at both. Many thanks for any hints.