Re: Fw: Clustering::Distance.php

From: "Jesus M. Castagnetto" <jcastagnetto@yahoo.com> > Nice class Alfredo. Thanks Jesus! > > please feel free to make any comments that you think might help to PEARIZE > > this code w/o harming efficience. > > The code looks OK to me (on a very quick glance). The advantage of having on > monolitical Distance class is that you can calculate different metrics on the > same data set. The disadvantage could be in the addition of more > metrics/similarity indeces. At the moment I would go for your solution, if and > when things get too complicated, then the class can be changed to use a factory > method. Well, I have a wish of (someday?) coding the distance functions in c, quite sure that as Zend's got them they'll behave quite speedy! As you saw on the class, there's an array with metric names and function names, so the idea behind this is that the class may allow to add new metrics, just by refering their function names in this structure. These functions could be members of the class, system functions or part of a library written in php, and the class will surely provide a means for handling measures in a whole data set, and can be asked about "what metrics do you got?". The factory method is nice, but I'm not quite sure to understand in which we can use it here. > > please review it, and make any comments you like!! > > I can suggest some names for the class, because those metrics are generalized > distances, which can be used for clustering or other purposes: > > Math_DistanceMetric > > or > > Math_Cluster_Distance > > or > > Math_Distance > > Then the Math_Cluster class(es) can use the Math_Cluster)_Distance (or > Math_DistanceMetric) object(s) I totally agee with you. At this time I was thinking the same thing, because there are many applications for distance metrics. I think that Math_Distance would do it fine, as short. And I think: Would it be necessary (or just cool?) that the Math_Distance package provides an interface for measuring between Math_Vector objects? Consider also that the kind of objects we're going to compare are not necesarilly vectors in R^d, but can be also binary vectors and binary objects, such as strings (what about natural language processing in php?). > BTW, there are several metrics I did not know, but found this on Google: > > http://geochange.er.usgs.gov/pub/tools/analog/doc/distance.html > > http://fconyx.ncifcrf.gov/~lukeb/clusdis.html Well, there's a lot of this stuff! http://astro.u-strasbg.fr/~fmurtagh/mda-sw/online-sw.html > > There are other simple metrics for vectors, which might not need to be there, > but that I might add as a utility class for Math_Vector: City block distance > (aka Manhattan distance) and Chessboard Distance. > > City dist = |x1 - x2| + |y1 - y2| + ... > > Chessboard dist. = max(|x1 - x2|, |y1 - y2|, ...) Well, I'll take a look as Math_Vector because Manhattan is a nice norm to implement here. One of the applications I've thought for this proyect is to deploy a SOAP clustering/measurement service, so as much options it has, the more helpful it would be for the intended audiences (mathematicians, biologists, chemistrians, etc). Also, there's a whole bunch of different metrics, many of which don't operate on R^d objetcs, but between binary objects and binary vectors; and also methods for measuring graph distances would be useful. In another order of ideas, and with the proper respect to the list: How can I obtain a CVS account on Pear? Saludos Alfredo Rahn