patternclassify.asv

我ANN的大作业

function PatternClassify(X2s_train, X2s_test)

[row,col] = size(X2s_train);

%提取训练数据和测试数据
input_P = 2s_train(:,1:col-1);
target_T = 2s_train(:,col);
test_P = 2s_test(:,1:col-1);
test_T = 2s_test(:,col);

%训练三层神经网络,隐藏层有10个单元
eps = 0.1;
alpha = 0.1;
initU1 = [0.43 0.54 
          0.23 0.54 
          0.54 0.54 
          0.53 0.22 
          0.15 0.98
          0.67 0.23 
          0.34 0.65 
          0.54 0.34 
          0.11 0.87 
          0.34 0.45];
initV1 = [0.43 0.56 
          0.24 0.5 
          0.54 0.26 
          0.76 0.87 
          0.26 0.38
          0.38 0.48 
          0.26 0.1 
          0.48 0.38 
          0.85 0.48 
          0.96 0.59];
initb1 = [0.42;0.23;0.31;0.43;0.42;0.34;0.43;0.23;0.12;0.43];

initU2 = [0.5 0.55 0.32 0.21 0.23 0.6 0.1 0.21 0.43 0.87];
initV2 = [0.4 0.32 0.52 0.36 0.14 0.9 0.45 0.21 0.78 0.11];
initb2 = [0.1];

[u1,u2, v1, v2, b1, b2, times] = MLP(eps, initU1, initV1, initb1, initU2, initV2, initb2 , alpha, input_P, target_T)

%验证神经网络的正确性
len = length(test_T);
correct = 0;
for i=1:len
    x0 = test_P(i,:)';
    x1 = sigmoid(u1*(x0.^2) + v1*x0 + b1);
    x2 = sigmoid(u2*(x1.^2) + v2*x1 + b2);
    if(round(x2)==test_T(i))
        correct = correct+1;
    end
end
correct