function scores=main()
trainSet=[0 0;1 1;2 2; 3 3; 4 4];
testSet=[1 1;1 5 ;1 7];
scores(1,1)=evaluate(@buildAverageModel,0,trainSet,testSet);
scores(2,1)=evaluate(@buildKNNModel,1,trainSet,testSet);
scores(3,1)=evaluate(@buildKNNModel,2,trainSet,testSet);
scores(4,1)=evaluate(@buildKNNModel,3,trainSet,testSet);
scores(5,1)=evaluate(@buildKNNModel,4,trainSet,testSet);

trainSet=[1 1 1; 3 3 1; 4 4 4; 3 4 2; 4,3,3];
testSet=[5 5 5; 1 3 2];
scores(1,2)=evaluate(@buildAverageModel,0,trainSet,testSet);
scores(2,2)=evaluate(@buildKNNModel,1,trainSet,testSet);
scores(3,2)=evaluate(@buildKNNModel,2,trainSet,testSet);
scores(4,2)=evaluate(@buildKNNModel,3,trainSet,testSet);
scores(5,2)=evaluate(@buildKNNModel,4,trainSet,testSet);

auto_data=load('auto-csv.csv');
model=buildAverageModel(auto_data);

%Output the average MPG in whatever way is appropriate
scores(1,3)=model;

[N d]=size(auto_data);
auto_train=auto_data(1:N/2,:);
auto_test=auto_data(N/2+1:N,:);

[model,f]=buildKNNModel(auto_train,4);
scores(2,3)=f(model,auto_test(5,1:d-1));
scores(3,3)=evaluate(@buildKNNModel,4,auto_train,auto_test);
scores(4,3)=evaluate(@buildKNNModel,1,auto_train,auto_train);
scores(5,3)=123;

%output is a 5x3 matrix