On Thu, 29 Jun 2017, Alex Byrley writes: > I am looking for packages that can run a branch-and-bound algorithm to > maximize a distance measure (such as Bhattacharyya or Mahalanobis) on a set > of features. > > I would like this to be learning algorithm independent, so that the method > just looks at the features, and selects the subset of a user-defined size > that maximizes a distance criteria such as those stated above. > > Can anyone give some suggestions? > > Alex Byrley > Graduate Student > Department of Electrical Engineering > 235 Davis Hall > (716) 341-1802 >
It seems you are looking for a generic optimisation algorithm; so perhaps start at the task view: https://cran.r-project.org/web/views/Optimization.html What you describe is a combinatorial problem: select k from N features, with k (much) smaller than N. So I'd suggest to also look at heuristic algorithms that can deal with such problems (e.g. genetic algorithms). -- Enrico Schumann Lucerne, Switzerland http://enricoschumann.net ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
