[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.