tic?%?計時器
%%?清空環境，準備數據
close?all
clear
clc
format?compact
%?載入測試數據wine其中包含的數據類別數為3；wine:178*13的矩陣wine_labes:178*1的列向量
load?wine
%?選定訓練集和測試集
%?將第一類的1-30第二類的60-95第三類的131-153做為訓練集
train_wine?=?[wine（1:30:）;wine（60:95:）;wine（131:153:）];
%?相應的訓練集的標簽也要分離出來
train_wine_labels?=?[wine_labels（1:30）;wine_labels（60:95）;wine_labels（131:153）];
%?將第一類的31-59第二類的96-130第三類的154-178做為測試集
test_wine?=?[wine（31:59:）;wine（96:130:）;wine（154:178:）];
%?相應的測試集的標簽也要分離出來
test_wine_labels?=?[wine_labels（31:59）;wine_labels（96:130）;wine_labels（154:178）];
%?數據預處理
%?數據預處理將訓練集和測試集歸一化到[01]區間
[mtrainntrain]?=?size（train_wine）;
[mtestntest]?=?size（test_wine）;
dataset?=?[train_wine;test_wine];

[dataset_scaleps]?=?mapminmax（dataset‘01）;
dataset_scale?=?dataset_scale‘;

train_wine?=?dataset_scale（1:mtrain:）;
test_wine?=?dataset_scale（?（mtrain+1）:（mtrain+mtest）:?）;
%%?CS-SVM
time=20;
n=20;?%?n為巢穴數量
pa=0.25;?%?被宿主發現的概率
dim?=?2;?%?需要尋優的參數個數
Lb=[0.010.01];?%?設置參數下界
Ub=[100100];?%?設置參數上界

%?隨機初始化巢穴
nest=zeros（ndim）;
for?i=1:n?%?遍歷每個巢穴
????nest（i:）=Lb+（Ub-Lb）.*rand（size（Lb））;?%?對每個巢穴，隨機初始化參數
end

fitness=ones（1n）;?%?目標函數值初始化
[fminbestnestnestfitness]=get_best_nest_svm（nestnestfitnesstrain_wine_labelstrain_winetest_wine_labelstest_wine）;?%?找出當前最佳巢穴和參數

%%?迭代開始
for?t=1:time
????new_nest=get_cuckoos（nestbestnestLbUb）;?%?保留當前最優解，尋找新巢穴
????[~~nestfitness]=get_best_nest_svm（nestnew_nestfitnesstrain_wine_labelstrain_winetest_wine_labelstest_wine）;?%?找出當前最佳巢穴和參數
????new_nest=empty_nests（nestLbUbpa）;?%?發現并更新劣質巢穴
????%?找出當前最佳巢穴和參數
????[fnewbestnestfitness]=get_best_nest_svm（nestnew_nestfitnesstrain_wine_labelstrain_winetest_wine_labelstest_wine）;?
????if?fnew????????fmin=fnew;
????????bestnest=best?;
????end
end
%%?打印參數選擇結果
bestobjfun=fmin;
bestc=bestnest（1）;
bestg=bestnest（2）;
disp（‘打印參數選擇結果‘）;
str=sprintf（‘Best?c?=?%g，Best?g?=?%g‘bestcbestg）;
disp（str）
%%?利用最佳的參數進行SVM網絡訓練
cmd_gwosvm?=?[‘-c?‘num2str（bestc）‘?-g?‘num2str（bestg）];
model_gwosvm?=?svmtrain（train_wine_labelstrain_winecmd_gwosvm）;
%%?SVM網絡預測
[predict_labelaccuracy]?=?svmpredict（test_wine_labelstest_winemodel_gwosvm）;
%?打印測試集分類準確率
total?=?length（test_wine_labels）;
right?=?sum（predict_label?==?test_wine_labels）;
disp（‘打印測試集分類準確率‘）;
str?=?sprintf（?‘Accuracy?=?%g%%?（%d/%d）‘accuracy（1）righttotal）;
disp（str）;
%%?結果分析
%?測試集的實際分類和預測分類圖
figure;
hold?on;
plot（test_wine_labels‘o‘）;
plot（predict_label‘r*‘）;
xlabel（‘測試集樣本‘‘FontSize‘12）;
ylabel（‘類別標簽‘‘FontSize‘12）;
legend（‘實際測試集分類‘‘預測測試集分類‘）;
title（‘測試集的實際分類和預測分類圖‘‘FontSize‘12）;
grid?on
snapnow
%%?顯示程序運行時間
toc

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2016-09-05?17:22??CS-SVM\
?????文件????????3051??2016-09-05?17:22??CS-SVM\CS_SVM_exmp.m
?????文件????????2716??2016-09-05?17:00??CS-SVM\CS_SVR_exmp.m
?????文件????????6483??2016-09-05?16:52??CS-SVM\cuckoo_ori_with_chinese_note.m
?????文件?????????999??2016-09-05?16:49??CS-SVM\empty_nests.m
?????文件?????????426??2016-09-05?16:49??CS-SVM\fobj.m
?????文件?????????676??2016-09-05?17:22??CS-SVM\get_best_nest.m
?????文件?????????698??2016-09-05?17:21??CS-SVM\get_best_nest_svm.m
?????文件????????1629??2016-09-05?16:49??CS-SVM\get_cuckoos.m
?????文件??????????70??2016-09-05?16:49??CS-SVM\mymae.m
?????文件??????????85??2016-09-05?16:49??CS-SVM\mymape.m
?????文件??????????74??2016-09-05?16:49??CS-SVM\mymse.m
?????文件?????????402??2016-09-05?17:13??CS-SVM\objfun.m
?????文件?????????376??2016-09-05?16:49??CS-SVM\simplebounds.m
?????文件???????20168??2016-09-05?17:17??CS-SVM\wine.mat
?????文件?????????447??2016-09-05?16:49??CS-SVM\wndspd.mat
?????目錄???????????0??2016-09-05?16:45??PSO-SVM\
?????文件?????????426??2016-09-05?16:14??PSO-SVM\fobj.m
?????文件?????????108??2016-09-05?15:04??PSO-SVM\fun.m
?????文件??????????70??2016-09-05?16:14??PSO-SVM\mymae.m
?????文件??????????85??2016-09-05?16:14??PSO-SVM\mymape.m
?????文件??????????74??2016-09-05?16:14??PSO-SVM\mymse.m
?????文件?????????402??2016-09-05?17:12??PSO-SVM\objfun.m
?????文件????????4106??2016-09-05?16:43??PSO-SVM\PSO_SVM_exmp.m
?????文件????????3814??2016-09-05?17:00??PSO-SVM\PSO_SVR_exmp.m
?????文件????????2276??2016-09-05?16:11??PSO-SVM\pso_test.m
?????文件???????20168??2016-09-05?16:37??PSO-SVM\wine.mat
?????文件?????????447??2016-09-05?16:14??PSO-SVM\wndspd.mat