I have a table: https://imgur.com/a/TZAhF The columns represent weight of groceries in a room, the rows represent temperature of the room. The values represent a likelihood the food goes bad (it's some original likelihood I came up with, not percent).
Anyways, I now have new data that I want to classify using my table. Based on whatever row and column combnation the new data point lands in, I will use that to determine predicted likelihood.
I guess this isn't exactly k nearest neighbors, but the idea is kind of similar. What would this method be called? And are these any specific statistical issues I need to look out for?