分類預(yù)測(cè) | MATLAB實(shí)現(xiàn)WOA-FS-SVM鯨魚算法同步優(yōu)化特征選擇結(jié)合支持向量機(jī)分類預(yù)測(cè)
效果一覽
基本介紹
MATLAB實(shí)現(xiàn)WOA-FS-SVM鯨魚算法同步優(yōu)化特征選擇結(jié)合支持向量機(jī)分類預(yù)測(cè)（完整程序和數(shù)據(jù)）
WOA鯨魚算法同步優(yōu)化特征選擇結(jié)合支持向量機(jī)分類預(yù)測(cè)，優(yōu)化前后對(duì)比，基于LIBSVM。文章來源：http://www.zghlxwxcb.cn/news/detail-730383.html
程序設(shè)計(jì)
- 完整程序和數(shù)據(jù)下載方式私信博主回復(fù)：MATLAB實(shí)現(xiàn)WOA-FS-SVM鯨魚算法同步優(yōu)化特征選擇結(jié)合支持向量機(jī)分類預(yù)測(cè)
%% 參數(shù)設(shè)置
% 定義優(yōu)化參數(shù)的個(gè)數(shù)，在該場(chǎng)景中，優(yōu)化參數(shù)的個(gè)數(shù)為數(shù)據(jù)集特征總數(shù) 。
%目標(biāo)函數(shù)
fobj = @(x) fun(x,train_wine_labels,train_wine,test_wine_labels,test_wine);
% 優(yōu)化參數(shù)的個(gè)數(shù) 特征維度
dim = size(train_wine,2); %特征維度
% 優(yōu)化參數(shù)的取值下限，[0,1],大于0.5為選擇該特征，小于0.5為不選擇該特征
lb = 0;
ub = 1;
%% 參數(shù)設(shè)置
pop =10; %數(shù)量
Max_iteration=50;%最大迭代次數(shù)
%% 優(yōu)化(這里主要調(diào)用函數(shù))
[Best_score,Best_pos,curve]=WOA(pop,Max_iteration,lb,ub,dim,fobj);
figure
plot(curve,'linewidth',1.5);
xlabel('迭代次數(shù)');
ylabel('適應(yīng)度值');
title('收斂曲線');
grid on;
c = 2;
g = 2;
toc
% 用優(yōu)化得到的特征進(jìn)行訓(xùn)練和測(cè)試
cmd = ['-s 0 -t 2 ', '-c ', num2str(c), ' -g ', num2str(g), ' -q'];
model = libsvmtrain(train_wine_labels, train_wineNew, cmd);
test_wineNew = test_wine(:,B);
%% SVM網(wǎng)絡(luò)預(yù)測(cè)
[predict_labelTrain, accuracyTrain,~] = libsvmpredict(train_wine_labels, train_wineNew, model);
[predict_labelTest, accuracyTest,~] = libsvmpredict(test_wine_labels, test_wineNew, model);
%% 基礎(chǔ)SVM預(yù)測(cè)結(jié)果
% 用優(yōu)化得到的特征進(jìn)行訓(xùn)練和測(cè)試
cmd = ['-s 0 -t 2 ', '-c ', num2str(c), ' -g ', num2str(g), ' -q'];
model = libsvmtrain(train_wine_labels, train_wine, cmd);
%% SVM網(wǎng)絡(luò)預(yù)測(cè)
[predict_labelTrain1, accuracyTrain1,~] = libsvmpredict(train_wine_labels, train_wine, model);
[predict_labelTest1, accuracyTest1,~] = libsvmpredict(test_wine_labels, test_wine, model);%% 結(jié)果分析
參考資料
[1] https://blog.csdn.net/kjm13182345320/article/details/128163536?spm=1001.2014.3001.5502
[2] https://blog.csdn.net/kjm13182345320/article/details/128151206?spm=1001.2014.3001.5502文章來源地址http://www.zghlxwxcb.cn/news/detail-730383.html
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