README=======================================================================Incremental and decremental support vector machine learningMatlab code, data and demosG. Cauwenberghsgert@jhu.edu=======================================================================This directory contains Matlab code, data files, and example demos forincremental SVM classification, including exact leave-one-outcross-validation.  The file incremental.tar.gz contains the entiregzipped, tarred directory.To start, run test_2d or test_diabetes at the Matlab prompt.  Makesure to have all *.m and *.mat files in your directory.  Use theMatlab "help" function to find syntax and more information on theimplemented functions.  Some of the parameters are available as globalvariables in the workspace (see test*.m for examples).This software is in the public domain; there are no implied warrantiesof any kind!  Send bug reports to gert@jhu.eduMatlab functions and scripts:-----------------------------svcm_*.m     support vector classification machinekernel.m     kernel function used in svcm_*.mtest*.m      example demo scriptsSet*.m       graphics formattinggen*.m       data generating functionsMatlab data:------------*.mat        vectors x [L,N], and labels y [L,1] (-1 or 1)Sample output:--------------*.eps        encapsulated PostScriptReference:----------G. Cauwenberghs and T. Poggio, "Incremental and Decremental SupportVector Machine Learning," in Adv. Neural Information ProcessingSystems (NIPS*2000), Cambridge MA: MIT Press, vol. 13, 2001.(http://bach.ece.jhu.edu/pub/gert/papers/nips00_inc.pdf)