This post is slightly off-topic, but thought this forum is the best place to ask.
Here goes,let say I have a sequence of values …
Value X can be followed by any of “n” other values Y1,Y2,Y3, … Yn
When I arrive at X I predict one of the Y values. If I predict correctly I should get a reward, penalty otherwise.
In addition every visit to a value I increment a counter I keep for every value.
/Visits can be viewed as Probability … taking into account all Y’s/
So I have two pieces of information Probability and Predictability.
What I want is to create a score that combines this information AND also an update formula for this score.
I will use this score to “correctly” predict what is the most probable and correct value Y after X.
It is repeatable process, so the scores will change over time.
I’m looking for the most plausible and common sense interpretation i.e. the prediction should be based on how often value Yx followed X, but also how correctly it was predicted, unless you can persuade me otherwise.
My thinking is that this will better capture the fluid nature of change in what follows X over time.
/I can also for-see using discount factor somehow/
The best idea I had so far is that Predictability is an S-curve function [0 … 1 ] and the score is :
Score = Probability * Predictability
I would also prefer to hold/store single value as a Score, rather than two values which I combine.