There are a few important variables in my model with high variability across biological repeats. Is there any way to deal with this situation?
Let's take blood pressure as an example. I measure the blood pressure of one patient 2 times. Because of the limit of my equipment, I may get different numbers for the same patient. Moreover, I don't know the exact systematic errors for my measurements.
How to deal with this kind of features in building predictive models? If a new patient comes in, I can only measure his blood pressure once, how should I use this feature in my model to give a stable prediction?