src/test/scripts/functions/builtin/HyperbandLM3.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);
numTrSamples = 100;
numValSamples = 100;

X_train = X[1:numTrSamples,];
y_train = y[1:numTrSamples,];
X_val = X[(numTrSamples+1):(numTrSamples+numValSamples+1),];
y_val = y[(numTrSamples+1):(numTrSamples+numValSamples+1),];
X_test = X[(numTrSamples+numValSamples+2):nrow(X),];
y_test = y[(numTrSamples+numValSamples+2):nrow(X),];

params = list("reg");
paramRanges = matrix("0 20", rows=1, cols=2);

[bestWeights, optHyperParams] = hyperband(X_train=X_train, y_train=y_train,
  X_val=X_val, y_val=y_val, params=params, paramRanges=paramRanges);

paramRanges2 = list(10^seq(0,-4))
trainArgs = list(X=X_train, y=y_train, icpt=0, reg=-1, tol=1e-9, maxi=0, verbose=FALSE);
[bestWeights, optHyperParams2] = gridSearch(X=X_train, y=y_train, numB=ncol(X),
  train="lm", predict="l2norm", trainArgs=trainArgs, params=params, paramValues=paramRanges2);

print(toString(optHyperParams))
print(toString(optHyperParams2))