1nn -- pure matlab

1nn.m

% ... Xtrain/Xtest/ytrain/ytest/ntest/
tic
% sum of squares term for speed
XtrainSOS = sum(Xtrain.^2,2);
XtestSOS  = sum(Xtest.^2,2);

ypred = zeros(ntest,1);
% Classify
dst = sqDistance(Xtest(:,:),Xtrain,XtestSOS(:,:),XtrainSOS);
[~,closest] = min(dst,[],2); 
ypred = ytrain(closest);
% Report
errorRate = mean(ypred ~= ytest);
fprintf('Error Rate: %.2f%%\n',100*errorRate);
t = toc; fprintf('Total Time: %.2f seconds\n',t);

although it only need 4 sec to run, the code may use lots of memory...