Hi Corrado, I was thinking about this some more.
Maybe you could use a linear discriminate, i.e. a (hyper)plane that partitions your points into two sets, such that the misclassification rate is minimised. Closeness could be regarded as the number of misclassified points. Two sets would be distant, if no points are misclassified. I am assuming there is a standard function in R to do this, no idea what it is though. Plus this is a reasonably well known technique. Again the size of the sets needs to be accounted for. As well as the question, does the distance of set A from B, need to be the same as the distance of set B from A. Both the nearest neighbour approach and the discriminant approach, don't necessarily satisfy this condition. regards -- Charlotte Maia http://sites.google.com/site/maiagx/home ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
