c_svc_sim.m

各人用Mtalab编写的SVM程序

function Yd = C_SVC_Sim(svm,Xt)
% 输入参数:
% svm 支持向量机(结构体变量)
% the following fields:
% ker - 核参数
% type - linear : k(x,y) = x'*y
% poly : k(x,y) = (x'*y+c)^d
% gauss : k(x,y) = exp(-0.5*(norm(x-y)/s)^2)
% tanh : k(x,y) = tanh(g*x'*y+c)
% degree - Degree d of polynomial kernel (positive scalar).
% offset - Offset c of polynomial and tanh kernel (scalar, negative for tanh).
% width - Width s of Gauss kernel (positive scalar).
% gamma - Slope g of the tanh kernel (positive scalar).
% x - 训练样本
% y - 训练目标;
% a - 拉格朗日乘子
%
% Xt 测试样本,n×d的矩阵,n为样本个数,d为样本维数

% 输出参数:
% Yd 测试输出,n×1的矩阵,n为样本个数,值为+1或-1

% ------------------------------------------------------------%

ker = svm.ker;
X = svm.x;
Y = svm.y;
a = svm.a;

% ------------------------------------------------------------%
% 求 b

epsilon = 1e-8; % 如果小于此值则认为是0
i_sv = find(a>epsilon); % 支持向量下标

tmp = (Y.*a)'*Calckernel(ker,X,X(i_sv,:)); % 行向量
b = 1./Y(i_sv)-tmp';
b = mean(b);

% ------------------------------------------------------------%
% 测试输出

nt = size(Xt,1); % 测试样本数
tmp = (Y.*a)'*Calckernel(ker,X,Xt);
Yd = sign(tmp+b)';