<span style="font-size:18px;">%% 清空環境變量 clear all clc warning off %% 導入數據 load data.mat a=randperm(569); Train=data(a(1:500),:); Test=data(a(501:end),:); % 訓練數據 P_train=Train(:,3:end)'; Tc_train=Train(:,2)'; T_train=ind2vec(Tc_train); % 測試數據 P_test=Test(:,3:end)'; Tc_test=Test(:,2)'; %% 創建網絡 count_B=length(find(Tc_train==1)); count_M=length(find(Tc_train==2)); rate_B=count_B/500; rate_M=count_M/500; net=newlvq(minmax(P_train),20,[rate_B rate_M],0.01,'learnlv1'); % 設置網絡參數 net.trainParam.epochs=1000; net.trainParam.show=10; net.trainParam.lr=0.1; net.trainParam.goal=0.1; %% 訓練網絡 net=train(net,P_train,T_train); %% 仿真測試 T_sim=sim(net,P_test); Tc_sim=vec2ind(T_sim); result=[Tc_sim;Tc_test] %% 結果顯示 total_B=length(find(data(:,2)==1)); total_M=length(find(data(:,2)==2)); number_B=length(find(Tc_test==1)); number_M=length(find(Tc_test==2)); number_B_sim=length(find(Tc_sim==1 & Tc_test==1)); number_M_sim=length(find(Tc_sim==2 &Tc_test==2)); disp(['病例總數：' num2str(569)...' 良性：' num2str(total_B)...' 惡性：' num2str(total_M)]); disp(['訓練集病例總數：' num2str(500)...' 良性：' num2str(count_B)...' 惡性：' num2str(count_M)]); disp(['測試集病例總數：' num2str(69)...' 良性：' num2str(number_B)...' 惡性：' num2str(number_M)]); disp(['良性乳腺腫瘤確診：' num2str(number_B_sim)...' 誤診：' num2str(number_B-number_B_sim)...' 確診率p1=' num2str(number_B_sim/number_B*100) '%']); disp(['惡性乳腺腫瘤確診：' num2str(number_M_sim)...' 誤診：' num2str(number_M-number_M_sim)...' 確診率p2=' num2str(number_M_sim/number_M*100) '%']); </span>

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