closest_average.m

%Closest average training error rate is 20%.
%Closest average test error rate is 17%.

%This function takes in a training data matrix Xtrain, training
%label vector ytrain and uses them to compute the average cat
%and dog vectors. It also takes in a data matrix Xrun and 
%produces a vector of label guesses yguess, corresponding to whether
%each row of Xtest is closer to the average cat or average dog.
function yguess = closest_average(Xtrain,ytrain,Xrun)

[row, col] = size(Xrun);
yguess = zeros(row, 1);

[avgcat avgdog] = average_pet(Xtrain,ytrain);

for i = 1:row
    if (norm(Xrun(i,:) - avgcat) > norm(Xrun(i,:) - avgdog))
        yguess(i) = 1;
    else
        yguess(i) = -1;
    end
end

%Your code should go above this line.
if (~iscolumn(yguess))
    error("yguess is not a column vector.")
elseif (length(yguess)~=size(Xrun,1))
    error("Length of yguess is not equal to the number of rows in Xrun.")
elseif (sum(unique(abs(ytrain))~=1))
    warning("Some elements in ytrain are not +1 or -1.")
elseif (sum(unique(abs(yguess))~=1))
    warning("Some elements in yguess are not +1 or -1.")
end