查看文章

Intuitionistic fuzzy (IF) set theory combined with twin support vector machines (TSVM) has shown highly advantageous performance in robust and fast classification. However, the existing methods have some inherent flaws: 1) The inaccurate confidence caused by the single-center-based IF strategy degrades the classification performance of the model. 2) The nonmembership degree is time-consuming and the threshold is difficult to determine, as it depends on sample's local neighborhood set. 3) Recent theoretical studies have demonstrated that optimizing the margin distribution achieve better generalization performance than maximizing the minimum margin in SVM-based models (SVMs). In view of the aforementioned shortcomings, we propose a novel dual-center-based IF (DC-IF) function, and introduce the margin distribution into IFTSVM, forming a DC-IF twin bounded large margin distribution machines (DC …