Random forest probability meaning Lets say I trained a random forest on classes 0,1,2 as seen below.
Now I predict the classes probabilities with random forest for new points A and B.
Would I get...
For point A a probabilities classes of: 50% - class 0, 25% class 1, 25% class 2?
For point B a probabilities classes of: 90% - class 0, 5% class 1, 5% class 2?
In other words, does the class probability meaning is some kind of normalized distance between classes?
Now, let's say class 0 had only one point. Would this change the probabilities above?
Would appreciate if someone can put some light on this.
Thank!


See also this discussion about adjusting threshold and RF probability meaning citing a paper by Olson et al : Making Sense of Random Forest Probabilities: a Kernel Perspective
in which they "undertake an empirical investigation to determine the extent to which random forest parameter tuning influences its probability estimate"
