load iris_data.mat P_train = []; T_train = []; P_test = []; T_test = []; for i = 1:3 temp_input = features((i-1)*50+1:i*50,:); temp_output = classes((i-1)*50+1:i*50,:); n = randperm(50); P_train = [P_train temp_input(n(1:40),:)']; T_train = [T_train temp_output(n(1:40),:)']; P_test = [P_test temp_input(n(41:50),:)']; T_test = [T_test temp_output(n(41:50),:)']; end result_grnn = []; result_pnn = []; time_grnn = []; time_pnn = []; for i = 1:4 for j = i:4 p_train = P_train(i:j,:); p_test = P_test(i:j,:); t = cputime; net_grnn = newgrnn(p_train,T_train); t_sim_grnn = sim(net_grnn,p_test); T_sim_grnn = round(t_sim_grnn); t = cputime - t; time_grnn = [time_grnn t]; result_grnn = [result_grnn T_sim_grnn']; t = cputime; Tc_train = ind2vec(T_train); net_pnn = newpnn(p_train,Tc_train); Tc_test = ind2vec(T_test); t_sim_pnn = sim(net_pnn,p_test); T_sim_pnn = vec2ind(t_sim_pnn); t = cputime - t; time_pnn = [time_pnn t]; result_pnn = [result_pnn T_sim_pnn']; end end accuracy_grnn = []; accuracy_pnn = []; time = []; for i = 1:10 accuracy_1 = length(find(result_grnn(:,i) == T_test'))/length(T_test); accuracy_2 = length(find(result_pnn(:,i) == T_test'))/length(T_test); accuracy_grnn = [accuracy_grnn accuracy_1]; accuracy_pnn = [accuracy_pnn accuracy_2]; end result = [T_test' result_grnn result_pnn] accuracy = [accuracy_grnn;accuracy_pnn] time = [time_grnn;time_pnn]
转载于:https://www.cnblogs.com/yunyaniu/p/8424174.html
