Idea for geoguessr research/training
Thought id share a random idea i had :)
For every hint we see on geoguessr, there is a "positive predictive value" and "negative predictive value". E.g. Iceland bollards are a pretty strong hint youre in Iceland with no other clues needed because they don't really happen elsewhere.
This is quite useful to know when weighing up all the info and making a guess, how definitive each hint really is.
The trouble is we have to learn from lots of experience to make a judgement. And that is flawed as we will all have different experiences.
We have to search for the bad memory of that time when you were certain of something (that just wasnt true) and made a wrong guess. That time you saw .cz on a van and guessed Czechia but actually the van was in Slovakia or whatever.
My idea was that maybe machine learning could be used to work out these numbers, which might be helpful.
Might also help to notice the differences between hints found between different places e.g. Hungarian holey poles vs polish, Scottish bollards vs French (just an example, i know these can already be told apart).
It might get complicated quickly but would allow little mental flow charts e.g. x + y + z = particular region 95% of the time.
Im curious if this already exists or is technically possible!
TLDR: could machine learning show us how definitive each Geoguessr hint is?