function elmclass()
clear
P_train = load('F:\我\硕士研究生\本科毕设\已动手\1\experiment\train.txt')';
T_train = load('F:\我\硕士研究生\本科毕设\已动手\1\experiment\train_label.txt')';
P_test = load('F:\我\硕士研究生\本科毕设\已动手\abc.txt')';
%T_test = load('F:\我\硕士研究生\本科毕设\已动手\1\experiment\test_label.txt')';
[R,Q] = size(P_train);
a = P_train(1,:);
b = P_train(2,:);
c = P_train(3,:);
d = T_train;
[P_train,ps] = mapminmax(P_train ,0,1);
[P_test,ps] = mapminmax(P_test ,0,1);
% for i=1:Q %选择合适的隐含层节点数
% i=40;
%i=30;
% start_time_test=cputime;
[IW,B,LW,TF] = elmtrain(P_train,T_train,45,'sig');
% end_time_test=cputime;
%TestingTime=end_time_test-start_time_test;
T_sim_1 = elmpredict(P_train,IW,B,LW,TF);
% start_time_test=cputime;
Classification = elmpredict(P_test,IW,B,LW,TF)
%{
end_time_test=cputime;
TestingTime=end_time_test-start_time_test;
% result_1 = [T_train' T_sim_1'];
% result_2 = [T_test' T_sim_2'];
k1 = length(find(T_train == T_sim_1));
n1 = length(T_train);
Accuracy_1 = k1/n1*100;
disp(['训练集正确率=',num2str(Accuracy_1)]);
k2 = length(find(T_test == Classification));
n2 = length(T_test);
Accuracy_2(50) = k2/n2*100;
disp(['测试集正确率=',num2str(Accuracy_2)])
%}
%end
%{
figure
i=1:Q;
plot(i,Accuracy_1,'r');
legend('训练集正确率');
hold on
plot(i,Accuracy_2,'b');
legend('训练集正确率','测试集正确率');
%}
% figure
% [m,n] = size(T_test);
% plot(1:n,T_test,'bo')
% hold on
% plot(1:n,T_sim_2,'r*')
% legend('真实值','测量值');
end
