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ν-Improved nonparallel support vector machine
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DOI：10.1038/s41598-022-22559-5.png)
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Abstract
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In this paper, a nu-improved nonparallel support vector machine (nu-IMNPSVM) is proposed to solve binary classification problems. In this model, we use related ideas of nu-support vector machine(nu-SVM), the parameter nu is introduced to control the limits of the support vectors percentage. In the objective function, the parameter nu is increased to ensure that nu-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, nu-IMNPSVM can fully fit the distribution of data points in the class by minimizing the nu-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.
Keywords:
CLASSIFICATION
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