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Interval twin support vector regression algorithm for interval input-output data

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Abstract

It is necessary to use interval data to define terms or describe extreme behaviors because of the existence of uncertainty in many real-world problems. In this paper, a novel efficient interval twin support vector regression (ITSVR) is proposed to handle such interval data. This ITSVR employs two nonparallel functions to identify the upper and lower sides of the interval output data, respectively, in which the Hausdorff distance is incorporated into the Gaussian kernel as the interval kernel for interval input data. Compared with other support vector regression (SVR)-based interval regression methods, such as the interval support vector interval regression networks (ISVIRN), this ITSVR algorithm is more efficient since only two smaller-sized QPPs are solved, respectively. The experimental results on several artificial datasets and three stock index datasets show the validity of ITSVR.

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Acknowledgments

The authors thank the anonymous reviewers for their constructive comments and suggestions. This work is supported by the program of Shanghai Normal University (DZL121), the National Natural Science Foundation of Shanghai (12ZR1447100), the Natural Science Foundation of China (61202156), and the Natural Science Foundation of Zhejiang Province of China (Y6100588).

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Authors and Affiliations

  1. Department of Mathematics, Shanghai Normal University, Shanghai, 200234, People’s Republic of China

    Xinjun Peng, Dongjing Chen, Lingyan Kong & Dong Xu

  2. Scientific Computing Key Laboratory of Shanghai Universities, Shanghai, 200234, People’s Republic of China

    Xinjun Peng

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  1. Xinjun Peng
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  2. Dongjing Chen
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  3. Lingyan Kong
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  4. Dong Xu
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Correspondence to Xinjun Peng.

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Peng, X., Chen, D., Kong, L. et al. Interval twin support vector regression algorithm for interval input-output data. Int. J. Mach. Learn. & Cyber. 6, 719–732 (2015). https://doi.org/10.1007/s13042-015-0395-9

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  • DOI: https://doi.org/10.1007/s13042-015-0395-9

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