[Formula: see text]-Improved nonparallel support vector machine.

In this paper, a [Formula: see text]-improved nonparallel support vector machine ([Formula: see text]-IMNPSVM) is proposed to solve binary classification problems. In this model, we use related ideas of [Formula: see text]-support vector machine([Formula: see text]-SVM), the parameter [Formula: see text] is introduced to control the limits of the support vectors percentage. In the objective function, the parameter [Formula: see text] is increased to ensure that [Formula: see text]-band is kept as small as possible. It has played a great role in the classification of unbalanced data sets. On the basis of maximizing the interval between two classes, [Formula: see text]-IMNPSVM can fully fit the distribution of data points in the class by minimizing the [Formula: see text]-band, which enhances the generalization ability of the model. The results on the benchmark datasets testify that the proposed model has a good effect on the classification accuracy.