Algorithm 1 SCoRS

X ← DataMatrix(ntrain, p);

Y ← LabelsVector(ntrain);

r ← 0;

si = 0 and ci = 0, ∀i, i = 1 : p;

repeat

Randomly select a subset of features rp out of p;

ci(rp) ← ci(rp) + 1;

Randomly select a subset of examples rn out of ntrain;

RX ← X(rn, rp);

Apply regression to RX;

si ← si + 1∀i∣βi ≠ 0

r ← r + 1;

until r = R

Select feature i if (si./ci) > th, where 0 < th < 1 is a threshold value;