gusucode.com > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM源码程序 > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM\stprtool\svm\kmatrix.m
% KMATRIX computes kernel matrix for given data. % [K] = kmatrix( data, ker, arg ) % [K] = kmatrix( dataA, dataB, ker, arg ) % % Two cases: % 1) K(i,j) = kernel( data(:,i), data(:,j)) i,j=1,...,N % or % 2) K(i,j) = kernel( dataA(:,i), dataB(:,j)) i=1,...,N1, j=1,...,N2 % % Example: for 'linear' kernel it returns 1) data'*data % or 2) dataA'*dataB. % % Inputs: % 1) data [D x N ] matrix of N training D-dimensional patterns. % or % 2) dataA [D x N1 ] matrix of N1 training D-dimensional patterns. % dataB [D x N2 ] matrix of N2 training D-dimensional patterns. % % ker [string] kernel identifier. % arg [real] kernel argument. % % ker arg Kernel function % ----------------------------------------------------------------- % 'linear' [] Linear kernel: k(a,b) = a'*b % 'poly' d [int] Polynom: k(a,b)=(a'*b +1)^d % 'rbf' s [real] Radial Basis Functions: k(a,b)=exp^(0.5*||a-b||^2/s^2) % % Outputs: % 1) K [N x N] kernel matrix. % or % 2) K [N1 x N2] kernel matrix. % % Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac % (c) Czech Technical University Prague, http://cmp.felk.cvut.cz % Written Vojtech Franc (diploma thesis) 02.11.1999 % % Modifications. % 13-sep-2002, VF % 21-October-2001, V.Franc % 2-October-2001, V.Franc, created.