laplacian_score.asv

来自「利用支持向量回归进行概率密度估计」· ASV 代码 · 共 46 行

path(path,'C:\Documents and Settings\songjing\桌面\论文试验相关\dataset')
load dataset_wine.mat
f=dataset_wine.dataset;
total_sample_num=dataset_wine.total_sample_num;
dim_of_sample=dataset_wine.dim_of_sample;
s=zeros(total_sample_num,total_sample_num);
d=eye(total_sample_num,total_sample_num);

t=0.01;
for i=1:total_sample_num
    for j=1:total_sample_num
        a=(f(:,i)-f(:,j));
        s(i,j)=exp(-(a'*a)/t);
    end
end
o=linspace(1,1,total_sample_num);
L=zeros(dim_of_sample);
% norm(s(1,:),2)

for i=1:total_sample_num
           d(i,i)=dot(s(i,:),o);
end



for r=1:dim_of_sample
    numerator=0;
    denominator=0;
    mean=dot(f(r,:),o)/total_sample_num;
for i=1:total_sample_num
    for j=1:total_sample_num
        numerator=numerator+(f(r,i)-f(r,j))*(f(r,i)-f(r,j))*s(i,j);
    end
    denominator=denominator+(f(r,i)-mean)*(f(r,i)-mean)*d(i,i);
end


L(r)=numerator/denominator;
end
sort(L);
fix(rand(1)*755);