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In this paper, we propose a novel feature selection method which can suppress the input features during the process of model construction automatically. The main idea is to obtain better performance and sparse solutions by introducing Tikhonov regularization terms and measuring the objective function with $$L_1 $$ L1 -norm, based on projection twin support vector machine. Furthermore, to make the...