Abstract
Selection of proper kernel function for SVM is quite a difficult task. The paper presents the SVM with kernel generated by neuro-fuzzy system (NFS). The kernel function created in this way satisfies the Mercer’s theorem. The paper is accompanied by numerical results showing the ability of NFS to approximate the appropriate kernel functions.
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Simiński, K. (2014). Neuro-Fuzzy System Based Kernel for Classification with Support Vector Machines. In: Gruca, D., Czachórski, T., Kozielski, S. (eds) Man-Machine Interactions 3. Advances in Intelligent Systems and Computing, vol 242. Springer, Cham. https://doi.org/10.1007/978-3-319-02309-0_45
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DOI: https://doi.org/10.1007/978-3-319-02309-0_45
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02308-3
Online ISBN: 978-3-319-02309-0
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