Sometimes data sets contain variables that indicate the presence of an event and the value that represented the event.
As an example say a teacher wants to predict the grades of his students. Some of the students may have been in his class last year and he can use that grade as a variable. However maybe only 20% of the students were in his class so the rest of the 80% will have a Null value. Most ML algorithms cannot accept Null values so the variable would have to somehow be imputed.
I cannot think of an imputation method that would make sense here, the standard mean/mode would imply that all students were in the class and since the variable is pretty unbalance and 80% of the values would be imputed I don't imagine it would hold any valuable information.
Are there any methods to deal with this scenario?