Question

谁研究过多核极限学习机，有没有matlab代码可以参考下

Answer 1

close all
if ~exist('aaa')||(aaa~=1)
clc
clear
%加入gabor工具箱
addpath gaborpca;
path_pos='.\pos\';
path_nes='.\nes\';
pos_dir=dir(path_pos);
nes_dir=dir(path_nes);

%构建一个gabor滤波器组
filter_bank = construct_Gabor_filters(8, 5, [128 128]);
%提取正样本得gabor特征
feature_pos_train=[];
for i=3:158
im=imread([path_pos pos_dir(i).name]);
im=rgb2gray(im);
im = imresize(im,[128 128],'bilinear'); %采用'bilinear'：采用双线性插值算法扩展为128*128
raw_feature = filter_image_with_Gabor_bank(im,filter_bank,32);%%提取小波特征
feature_pos_train=[feature_pos_train,raw_feature];
end

%提取负样本得gabor特征
feature_nes_train=[];
for i=3:174
im=imread([path_nes nes_dir(i).name]);
im=rgb2gray(im);
im = imresize(im,[128 128],'bilinear'); %采用'bilinear'：采用双线性插值算法扩展为128*128
feature_nes_train=[feature_nes_train,raw_feature];
end

p_train=[feature_pos_train,feature_nes_train];
t_train=[ones(156,1);2*ones(172,1)];

%对提取得gabor特征进行压缩降维处理
[mappedX, mapping]=pca(p_train,111);
p_train=mapping.M;

p_train=mapminmax(p_train',0,1)';

%载入极限学习机工具箱
addpath kernelelm %%添加极限学习机算法包

%训练极限学习机
[model_elm]=kernel_elm_muti_train(p_train',t_train', 'gaussian',3.5,10);%%根据训练中的目标得出模型
[TT,TrainingAccuracy] = kernel_elm_muti_predict(p_train',t_train',model_elm);

end

%测试视频
aaa=1;
raw_feature2=[];
for i=1:1200
X=imread(strcat('picture\',num2str(i),'.jpg'));
im=rgb2gray( X);
im = imresize(im,[128 128],'bilinear'); %采用'bilinear'：采用双线性插值算法扩展为128*128
feature222 = filter_image_with_Gabor_bank(im,filter_bank,32);%%提取小波特征
raw_feature2=[raw_feature2,feature222];
disp(sprintf('%i ',i));
end

raw_feature2=mapminmax(raw_feature2',0,1);
p_test=raw_feature2*mappedX;
p_test=mapminmax(p_test',0,1)';
[TT,TrainingAccuracy] = kernel_elm_muti_predict(p_test',ones(1200,1)',model_elm);

clc
%输出每帧图得计算结果
for i=1:1200
if(TT(i)==2)
disp(sprintf('第%i帧图正常',i));
else
disp(sprintf('第%i帧图报警',i));
end
end