这里给出加州住房的例子，大家转载时请尊重版权，本例已列入新书《支持向量机的工程应用》，李应红，尉询楷编著，新书已正式开编，希望大家多提意见，

获得统计参数

for ii=1:100

cal_housing_data;

start=cputime;

%!svmtrain -s 0 -t 2 -g num2str(sigma) training.dat model.dat

dos(['svmtrain -s 3 -c 500 cal_housing_train.dat model.dat'])

train_time(ii)=cputime-start

params = libsvm2mat('model.dat');

No_sv(ii)=params.total_sv

dos(['svm-predict cal_housing_train.dat model.dat validation.txt'])

load validation.txt;

train_accuracy(ii)=sqrt(validation(end-1))

start1=cputime;

dos(['svm-predict cal_housing_test.dat model.dat validation1.txt'])

load validation1.txt

test_time(ii)=cputime-start1

test_accuracy(ii)=sqrt(validation1(end-1))

clear validation validation1 start start1;

end

av_train_time=mean(train_time);

dev_train_time=std(train_time);

av_test_time=mean(test_time);

dev_test_time=std(test_time);

av_train_accuracy=mean(train_accuracy);

dev_train_accuracy=std(train_accuracy);

av_test_accuracy=mean(test_accuracy);

dev_test_accuracy=std(test_accuracy);

av_No_sv=mean(No_sv);

save test1.mat;

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子程序

function params = libsvm2mat(fname)

%LIBSVM2MAT LibSVM to MATLAB conversion

% usage:

% params = libsvm2mat(model_file_name)

% or if you have a data file you would like to load

% params = libsvm2mat(data_file_name)

fid = fopen(fname,'r');

if (fid == -1), error(sprintf('%s not found!',fname')); end

while 1,

tline = fgetl(fid);

if ~ischar(tline), break, end

I = [findstr(tline,' ') length(tline)+1];

switch tline(1(1)-1),

case 'total_sv',

params.total_sv = sscanf(tline(I(1):end),'%f');

otherwise, % assume this to be a data file, double check if its true:

if isempty(str2num(tline(1(1)-1))),

disp([tline(1(1)-1) ' ignored!']);

else

k = 0;

while 1,

k = k + 1;

if ~ischar(tline), break, end

tline(find(tline == ':')) = ' ';

values = sscanf(tline, '%f')';

% params.y(k,1) = values(1);

%params.X(k, values(2:2:end)) = values(3:2:end);

tline = fgetl(fid);

end

end

end

end

fclose(fid);

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数据格式的生成

function cal_housing_data

%

%This file is used to load boston original data and generate random

%validation and test data.

% Created by skyhawk,2004.7.24

%

% function califonia_data

% %

%This file is used to load boston original data and generate random

%validation and test data.

% Created by skyhawk,2004.7.24

%

load cal_housing.data;

who

dataset=cal_housing;

rand_sequence=randperm(size(dataset,1));

temp_dataset=dataset;

dataset=temp_dataset(rand_sequence, ;

%预处理

for i=1:size(dataset,2)

if max(dataset(:,i))~=min(dataset(:,i))

dataset(:,i)= (dataset(:,i)-min(dataset(:,i)))/(max(dataset(:,i))-min(dataset(:,i)));

% dataset(:,i)=(dataset(:,i)-mean(dataset(:,i)))/(std(dataset(:,i)));

else

dataset(:,i)=0;

end

end

P1=dataset(1:8000,1:size(dataset,2)-1);

T1=dataset(1:8000,size(dataset,2));

%Obtain Random Validation Matrix

X=dataset(8001:size(dataset,1),1:size(dataset,2)-1);

Y=dataset(8001:size(dataset,1),size(dataset,2));

fid1 = fopen('cal_housing_train.dat','w');

for i=1:size(P1,1)

fprintf(fid1,'%2.8f ',T1(i,1));

for j=1:size(P1,2)

fprintf(fid1,' %d:%2.8f',j, P1(i,j)); % for SVM

end

fprintf(fid1,'\n');

end

fclose(fid1);

fid1 = fopen('cal_housing_test.dat','w');

for i=1:size(X,1)

fprintf(fid1,'%2.8f ',Y(i,1));

for j=1:size(X,2)

fprintf(fid1,' %d:%2.8f',j, X(i,j)); % for SVM

end

fprintf(fid1,'\n');

end

fclose(fid1);

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加州的数据网上查的到，大家可以验证