src/test/scripts/functions/builtin/GridSearchLM.dml

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l2norm = function(Matrix[Double] X, Matrix[Double] y, Matrix[Double] B) return (Matrix[Double] loss) {
  loss = as.matrix(sum((y - X%*%B)^2));
}

X = read($1);
y = read($2);
verbose = $4;

N = 200;
Xtrain = X[1:N,];
ytrain = y[1:N,];
Xtest = X[(N+1):nrow(X),];
ytest = y[(N+1):nrow(X),];

args = list(X=X, y=y, icpt=0, reg=-1, tol=-1, maxi=-1, verbose=FALSE);
params = list("reg", "tol", "maxi", "verbose");
paramRanges = list(10^seq(0,-4), 10^seq(-6,-12), 10^seq(1,3), as.matrix(as.double(verbose)));
[B1, opt] = gridSearch(X=Xtrain, y=ytrain, train="lm", predict="l2norm",
  numB=ncol(X), params=params, paramValues=paramRanges, trainArgs=args);
B2 = lm(X=Xtrain, y=ytrain, verbose=FALSE);

l1 = l2norm(Xtest, ytest, B1);
l2 = l2norm(Xtest, ytest, B2);
R = as.scalar(l1 < l2);

write(R, $3)