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% OSU Support Vector Machines (SVMs) Toolbox 
% version 3.00, Feb. 2002 
% 
% The core of this toolbox is based on Dr. Lin's Lib SVM version 2.33 
% For more details, please see: 
%  http://www.csie.ntu.edu.tw/~cjlin/libsvm 
% 
% Data Preprocessing: 
% 
%  Normalize: normalize all the samples to make their energy is 1 
%  Scale: scale all the samples to a range, such as [-1 1] 
% 
% SVM classifier Trainer: 
% 
%   LinearSVC (u_LinearSVC)  
%           - construct a linear C-SVM (nu-SVM) classifier  
%               from training samples. 
%   PolySVC (u_PolySVC) 
%           - construct a non-linear C-SVM (nu-SVM) classifier  
%             with a polynomial kernel. 
%   RbfSVC (u_RbfSVC) 
%           - construct a non-linear C-SVM (nu-SVM) classifier  
%            with a radial based kernel, or Gaussian kernel. 
%   one-RbfSVC 
%           - construct a non-linear 1-SVM with a radial based  
%             kernel, or Gaussian kernel. 
% 
% C-SVC Tester: 
% 
%   SVMTest - test the performance of a trained  
%                SVM classifier %
%  
% C-SVM Classifier: 
%    
%   SVMClass - classify a set of input patterns  
%                 given a trained SVM classifier % 
% Low level functions:  
% (following functions are called by functions listed above) 
%   SVMClass,  
%   mexSVMTrain, mexSVMClass 
% 
% Plot results: 
%   SVMPlot2: plot out the training samples and classification boundaries of a two-class problem 
%   SVMPlot: plot out the training samples and classification boundaries of a multi-class problem,  
%            However, generally speaking, the plots obtained by this function is not very attractive. 
% 
% Demonstration functions: 
%  Demo\osusvmdemo - the main function of the command-line demonstration 
% 
%  Demo\c_lindemo (u_lindemo)  
%           -  demonstration for constructing and test a linear C-SVM, or nu-SVM,  
%              classifier 
%  Demo\c_poldemo (u_poldemo) 
%           - demonstration for constructing and test a nonlinear C-SVM, or nu-SVM,  
%              classifier with a polynomial kernel 
%  Demo\c_rbfdemo (u_rbfdemo) 
%           - demonstration for constructing and test a nonlinear C-SVM, or nu-SVM, 
%              classifier with a RBF kernel 
%  Demo\one_rbfdemo  
%           - demonstration for constructing and test a nonlinear 1-SVM  
%             with a RBF kernel 
%  Demo\c_clademo (u_clademo) 
%           - demonstration for classify a group of input patterns using 
%             the constructed SVM classifier. 
%  Demo\DemoData_train, Demo\DemoData_test, and Demo\DemoData_class - data used 
%               in this demonstration. they are HRR radar signatures 
%               generated from MSTAR data. 
%---------------------------------------- 
% Authors:  
% Junshui Ma (junshui@lanl.gov), NIS-2, Los Alamos National Lab 
% Yi Zhao (zhaoy@ee.eng.ohio-state.edu), EE department, Ohio State University 
%