Extract from Andrew Moore's PhD Thesis: Ecient Memory-based Learning for Robot Control
PhD. Thesis; Technical Report No. 209, Computer Laboratory, University of Cambridge. 1991.
Table 6.4 describes my actual implementation of the nearest neighbour algorithm. It is called
with four parameters: the kd-tree, the target domain vector, a representation of a hyperrectangle in
Domain, and a value indicating the maximum distance from the target which is worth searching.
It’s been a really long time since I’ve read that paper. Thanks for the link and the call-out out 6.4. That “target distance worth searching” seems interesting when thinking about color-replacement.
[1991] https://www.ri.cmu.edu/pub_files/pub1/moore_andrew_1991_1/mo...
Table 6.4 describes my actual implementation of the nearest neighbour algorithm. It is called with four parameters: the kd-tree, the target domain vector, a representation of a hyperrectangle in Domain, and a value indicating the maximum distance from the target which is worth searching.