Dynamic Clustering - How many matches do you look for?
This is the thread's initial revision.
From what I understand of dynamic clustering, and the way I am currently looking at implementing mine, you store a history of all stats and which angles you would have hit the target at. Then when choosing your targeting angle you select the top N closest matches to the targets current state, and then select the angle to fire from those top N. My question is, does anyone have a good ballpark figure for the value of N?
If N is too small you might not have enough data about the target to get accuracy. If N is too large you might end up including too much information, polluting your pool with bad matches.
Or, do you not take N all the time, but instead only take matches which satisfy criteria on how good the match is, i.e only matches which are 5% different to the targets current state?
Anyone have opinions on this?
P.s If this is the wrong place to discuss, tell me and I will move it to the correct place! :)
