Hi
I have a more difficult problem and I'm not even sure where to start. I have an NxM matrix where m is the number of data sets I have.I want to group them in a "k-means"esque manner such that the differences between all partners are minimized, but only such that contiguous data sets are paired. The elligible information is housed in the structure "Neighbors" where the row number x=the data set, meaning [x,1] contains the eligible grouping partners.
How do i go about creating a program such that all collection of pairs will be quantified and the one with the least amount of differences will be returned, but which also takes into account the elligible pairs?