In this paper, a ν-improved nonparallel support vector machine (ν-IMNPSVM) is proposed to solve binary classification problems. In this model, we use the related ideas of ν-support vector machine(ν-SVM). The parameter ν is introduced to control the limits of the support vectors percentage. In the objective function, the parameter ε is introduced to ensure that ε-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, ν-IMNPSVM can fully fit the distribution of data points in the class by minimizing the ε-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.
AMS Subject Classification: 90C30