androidloadsvmraw,一些SVM的代码，有大神讲讲每一步具体实现了什么功能吗

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% Settings

rng(&＃39;shuffle&＃39;);

for data_set &＃61; 1:4

Dataset &＃61; num2str(data_set);

multilevel &＃61; 4;

ep_array &＃61; [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1];

C &＃61; 10;

Out_Local &＃61; fopen([Dataset,&＃39;_PrivLocal_SVM.txt&＃39;],&＃39;w&＃39;);

sh

RawData &＃61; load([&＃39;Data&＃39;,Dataset,&＃39;.dat&＃39;]);

[RawRow, RawCol] &＃61; size (RawData);

RawData_min &＃61; min(RawData,[],1);

RawData_max &＃61; max(RawData,[],1);

Data &＃61; (RawData-ones(RawRow,1)*RawData_min)./ (ones(RawRow,1)*(RawData_max-RawData_min)); % X,Y->[0,1]

Data &＃61; [(Data(:,1:end-1)-0.5).*2, ones(RawRow,1), (Data(:,end)-0.5).*2]; % X,Y->[-1,1]; add bias b

[DataRow, DataCol] &＃61; size (Data);

d &＃61; DataCol-1;

% Mutation settings

mutScale &＃61; 0.5;

mutResize &＃61; 0.95;

% End of Mutation setting

disp(&＃39;Start...&＃39;);

for stable &＃61; 1:10

fold &＃61; rand(DataRow, 1);

for foldnum &＃61; 1:5

SepLine &＃61; (0.2*(foldnum-1)

Test &＃61; Data(SepLine,:);

[TestRow, ~] &＃61; size(Test);

Train &＃61; Data(not(SepLine),:);

[TrainRow, ~] &＃61; size(Train);

for Epsilon &＃61; 1:10

ep &＃61; ep_array(Epsilon);

for multirun &＃61; 1:multilevel

disp([stable, foldnum, Epsilon, multirun]);

iteration &＃61; max(round( TrainRow*ep/800 ), 1);

disp(iteration);

seedsRemain &＃61; zeros(1, d);

Seeds &＃61; zeros(2*d, d);

curScale &＃61; mutScale;

for nextg &＃61; 1:d

mutation &＃61; zeros(1, d);

mutation(nextg) &＃61; curScale;

Seeds(nextg*2-1:nextg*2,:) &＃61; [seedsRemain&＃43;mutation; seedsRemain-mutation];

end

for it &＃61; 1:iteration

seedsUtility &＃61; SVMScore(Train, Seeds, C);

Sensitivity &＃61; 4*C*curScale;

seedsSelected &＃61; ExpMech(seedsUtility, ep/iteration, Sensitivity);

seedsRemain &＃61; Seeds(seedsSelected,:);

curScale &＃61; curScale * mutResize;

for nextg &＃61; 1:d

mutation &＃61; zeros(1, d);

mutation(nextg) &＃61; curScale;

Seeds(nextg*2-1:nextg*2,:) &＃61; [seedsRemain&＃43;mutation; seedsRemain-mutation];

end

end

Noised &＃61; SVMTest(Test, seedsRemain)/TestRow;

disp(Noised);

fprintf(Out_Local, &＃39;%d %d %d %d %e\n&＃39;, stable, foldnum, Epsilon, multirun, Noised);

end

end

end

end

end