Suppose you want to assign a noninformative prior to the following event:
The next tree that we will encounter is a:
- Spruce
- Pine
- None of the above
We don't have any prior information, so we are tempted to give each choice the same probability value, i.e. 1/3. But is this the right approach? Are there some general principles that scientists use to deal with "catch all else" categories?
Furthermore, suppose that we learn that a tree named Sequoia exists:
- Spruce
- Pine
- Sequoia
- None of the above
Now the question has four possible answers and the prior probability of "None of the above" has shrunk to 1/4. Same as the probability of any other tree. This somehow feels disturbing, because there is some inherent special status that "None of the above" should have. A Sequoia feels to have an affinity to a Spruce, but not to an abstract concept of "Any other tree".
Surely I am not the first person disturbed by this, so I would like to know if there are some general guidelines that one should follow when one category is defined negatively by all other categories.