Algorithm 1 SVM-RFE-OA

Input: training dataset X, t.

Output: selected feature subset FS.

Begin

c_acc = 0;

c_oa = ∞;

F = {all input features};

While (|F| > 0) Do

Construct an SVM based on X and F;

T_c_acc = d-fold cross validation accuracy rate of SVM;

T_c_oa = average Nr(x) of the samples in X based on F;

Rank the features in F by |w| in descending order;

If  T_c_acc − T_c_oa > c_acc − c_oa Then

c_acc = T_c_acc;

c_oa = T_c_oa;

FS = F;

Endif;

F = F− {t × |F| bottom ranked features in F};

Endwhile;

Return FS;

End.