I´d like to create a machine-learning classification model with caret based on MR-imaging data that I extract from a tumor. Lets assume that the tumor is composed of three different subregions (e.g. edema, necrosis, enhancement) and I extract several parameters (continuous variables) from these subregions. However, not every tumor shows necrosis so necrosis-related parameters cannot be calculated for some patients. How should I deal with this parameters so that I can include all patients (and all parameters) into my model?
- Excluding these patients would be an option, however I´d like to avoid it since I´d loose 10% of my sample size.
- Setting the values to NA and impute them is probably not the right solution (since the values are in not missing (in a classical sense), but simply cannot be calculated)
- Setting the values to "0" is probably also not recommended?
So is there any good method how I should deal with this situation so that I can include all parameters from all these patients into my machine-learning model?