Let's say that I want to predict a value Y that ranges between 0 and 1000. I have for this a set of features denoted X.
How would I force a machine learning model to be better on a specific range of my target. For example, if I want my model to be very good on values between 0 and 100, but it is okay if the model is not that good on values between 100 and 1000.
I am curious to know if there exists such technique. I would said that oversampling over the range of values that I am interested in would be good.