← Thread:User talk:MN/Hard-coded segmentation/reply (15)
This has been done a few times in the past. Various kD-Tree implementations have support for dynamically setting weightings for the distance function.
IIRC Diamond is one example of a bot that makes use of this feature of the kD-Tree implementation, though I think it does still use a pre-defined list rather than dynamic tweaking.
IIRC there have been experiments in dynamic weight tweaking but I'm not sure how successful they've been off hand.
You do not have permission to edit this page, for the following reasons:
- The action you have requested is limited to users in the group: Users.
- You must confirm your email address before editing pages. Please set and validate your email address through your user preferences.
You can view and copy the source of this page.Straw (talk)
Data decay (time classification) is one of many classifications in k-NN search. You need to mirror all of them to achieve perfect dodging.
You need a lot more data than is available to estimate all weights, unless you want to get shot a lot.
I believe multiple people have noted that the weight on new vs old data is significantly more important than weights on other predictors.(In a gun) I believe Skilgannon said something along the lines of: I can change the weights by tenfold (except the one on shots fired) and I get very little difference in performance. So if you could match that weight in your flattener, you could (hopefully) get very low hitrates against you.