Suppose you are trying to predict if lightning will strike in a given location in a given month. (Please ignore the meteorology here, this is not my actual problem, just a hypothetical instance of the general problem.)
So for each location, every day you compute some features like latitude, longitude, air pressure, etc. One feature that might be of interest is the number of days that have passed without a lightning strike.
Now suppose you have a location where lightning has not struck yet, but you still want to include it in your training data. The logically correct value for 'days_since_last_strike' is NULL. But your learning algorithm cannot handle NULL values.
What is a sensible value to replace NULL with?
I thought a negative number might work, but should it be -1, -9999, -INT_MAX? Is there a better solution?