sparsevariancestest.m.svn-base

a function inside machine learning

%Test sparse variances code 

clear;
rand('state',22); 

numExamples = 15; 
numFeatures = 10; 
tol = 10^-5; 

X = rand(numExamples, numFeatures); 
Y = sign(rand(numExamples, 1)-0.5); 

X = centerData(X); 

KX = X*X'; 

[variances, bs] = sparseVariances(KX, KX, Y, Y, (1:numExamples)'); 

variances2 = diag(KX*KX')./diag(KX);  
bs2 = 1./sqrt(diag(KX)); 

if norm(variances - variances2) > tol 
    error('Variances are wrong'); 
end 

if norm(bs - bs2) > tol 
    error('Scaling of dual directions are wrong'); 
end