支持向量机线性可分matlab程序

function model = svm0311(data,options) %SVM0311 解决2分类的SVM方法，优化使用matlab优化工具箱quadprog函数实现 %by LiFeiteng email:lifeiteng0422@gmail.com %Reference: stptool % Pattern Recognition and Machine Learning P333 7.32-7.37 % input aruments %------------------------------------------- tic % data=c2s(data); [dim,num_data]=size(data.X); % if nargin < 2, options=[]; else options=c2s(options); end if ~isfield(options,'ker'), options.ker = 'linear'; end if ~isfield(options,'arg'), options.arg = 1; end if ~isfield(options,'C'), options.C = inf; end if ~isfield(options,'norm'), options.norm = 1; end if ~isfield(options,'mu'), options.mu = 1e-12; end if ~isfield(options,'eps'), options.eps = 1e-12; end X = data.X; t = data.y; % t(t==2) = -1; % Set up QP task %---------------------------- K = X'*X; T = t'*t;% 注意t是横向量 H = K.*T; save('H0311.mat','H') H = H + options.mu*eye(size(H)); f = -ones(num_data,1); Aeq = t; beq = 0; lb = zeros(num_data,1); ub = options.C*ones(num_data,1); x0 = zeros(num_data,1); qp_options = optimset('Display','off'); [Alpha,fval,exitflag] = quadprog(H, f,[],[], Aeq, beq, lb, ub, x0, qp_options); inx_sv = find(Alpha>options.eps); % compute bias %-------------------------- % take boundary (f(x)=+/-1) support vectors 0 < Alpha < C b = 0; inx_bound = find( Alpha > options.eps & Alpha < (options.C - options.eps)); Nm = length(inx_bound); for n = 1:Nm tmp = 0; for m = 1:length(inx_sv) %PRML7.37 tmp = tmp+Alpha(inx_sv(m))*t(inx_sv(m))*K(inx_bound(n),inx_sv(m)); end b = b + t(inx_bound(n))-tmp; end b = b/Nm; model.b = b; %----------------------------------------- w = zeros(dim,1); for i = 1:num_data w = w+ Alpha(i)*t(i)*X(:,i);%PRML 7.29 end %% 画图，画出原始的分布 figure() gscatter(X(1,:),X(2,:),t,'rb','.'); hold on h(3) = plot(X(1, inx_sv),X(2, inx_sv),'ko'); % 画出支持向量 hold on ydata = 0:0.01:1; xdata = (-b - w(2)*ydata)/w(1); plot(xdata,ydata,'LineWidth', 2); % % d = 0.2; % [x1Grid,x2Grid] = meshgrid(min(X(:,1)):d:max(X(:,1)),... % min(X(:,2)):d:max(X(:,2))); % xGrid = [x1Grid(:),x2Grid(:)]; % % % % margin = 1/norm(w); % %------------------------------------------- % %此处与stprtool保持接口一致 用于画图展示等 % model.Alpha = Alpha( inx_sv ); % model.sv.X = data.X(:,inx_sv ); % model.sv.y = data.y(inx_sv ); % model.sv.inx = inx_sv; % model.nsv = length( inx_sv ); % model.margin = margin; % model.exitflag = exitflag; % model.options = options; % model.kercnt = num_data*(num_data+1)/2; % model.trnerr = cerror(data.y,svmclass(data.X, model)); % model.fun = 'svmclass'; % % model.W = model.sv.X*model.Alpha; % % % used CPU time model.cputime=toc; return;