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Reductive and effective discriminative information-based nonparallel support vector machine

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Abstract

In the paper, to improve the performance of discriminative information-based nonparallel support vector machine (DINPSVM), we propose a novel algorithm called reductive and effective discriminative information-based nonparallel support vector machine (REDINPSVM). First, we introduce the regularization term to achieve the structural risk minimization principle. This embodies the marrow of statistical learning theory, so this modification can enhance the generalization ability of classification algorithms. Second, we apply the k-nearest neighbor method to eliminate some redundant constraints that would cut down on time complexity. Finally, to accelerate the computation, we introduce the least squares technique to solve two systems of linear equations. Comprehensive experimental results on twenty-three UCI benchmark datasets and six Image datasets demonstrate the validity of the proposed method.

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Notes

  1. The prior data distribution information refers to the information obtained from the characteristic spatial distribution of known data.

  2. The prior discriminant information refers to the information obtained by bringing the known samples into the discriminant function.

  3. The space here refers to the feature space, and the prior spatial distribution information represents the information obtained from the characteristic spatial distribution of known data.

  4. http://archive.ics.uci.edu/ml/datasets.html

  5. https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary/skin_nonskin

  6. http://vision.stanford.edu/aditya86/ImageNetDogs/

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Acknowledgements

We gratefully thank the anonymous reviewers for their helpful comments and suggestions. This work was supported in part by the National Natural Science Foundation of China (No. 12071475) and the Fundamental Research Funds for the Central Universities (No. BLX201928).

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Authors and Affiliations

  1. College of Science, China Agricultural University, No. 17 Qinghua East Road, 100083, Haidian, Beijing, China

    Chunmei Wang & Zhijian Zhou

  2. College of Science, Beijing Forestry University, No. 35 Qinghua East Road, 100083, Haidian, Beijing, China

    Huiru Wang

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  1. Chunmei Wang
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  2. Huiru Wang
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  3. Zhijian Zhou
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Correspondence to Zhijian Zhou.

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Wang, C., Wang, H. & Zhou, Z. Reductive and effective discriminative information-based nonparallel support vector machine. Appl Intell 52, 8259–8278 (2022). https://doi.org/10.1007/s10489-021-02874-6

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