In binary classification problems, two classes of data seem to be different from each other. It is expected more complicated due the clusters in class also tend different. Traditional algorithms as Support Vector Machine (SVM) or Twin (TWSVM) cannot sufficiently exploit structural information with cluster granularity data, cause limitation on capability simulation trends. Structural (S-TWSVM) e...

Often, when dealing with real-world recognition problems, we do not need, and often cannot have, knowledge of the entire set possible classes that might appear during operational testing. In such cases, need to think robust classification methods able deal "unknown" properly reject samples belonging never seen training. Notwithstanding, existing classifiers date were mostly developed for closed...