"Rich Ulrich" <[EMAIL PROTECTED]> schreef in bericht news:[EMAIL PROTECTED] > On Tue, 02 Sep 2003 16:40:29 +0200, Cristian-Augustin Saita > <[EMAIL PROTECTED]> wrote: > > > Hello, > > > > Someone could tell me, please, if there exists any standard method of > > generating points in a multi-dimensional real hyper-space (like [0,1]^N, > > where N represents the number of dimensions) so to preserve the unknown > > space distribution of a given sample of points from the considered space. > > > > More precisely, based on a sample of 60,000 mutidimensional points > > (representing colour characteristics of images from an image database), > > is it possible to generate a set of 1,000,000 points with garanties (of > > any nature) that the generated set preserves the (unknown) space > > distribution of the original sample set? I want to avoid to simply > > replicate/duplicate the original points, method which I'm not very sure > > that preserves the original distribution either. > > You can draw from a collection of the original points. > > Or you can use the original points but make them blurry. > > Or you can derive parameters from the original points > and 'randomize' based on the parameters. > > Once you have said "No" those three things, alone and in > every combination, I can't think of anything to suggest, > except that you need to reconsider what you are trying > to achieve. >
Maybe you are looking for something like a "convex hull". Searching with Google on these keywords results in a lot of usefull references. Jos Jansen . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
