Kernel credal classification rule

Khawla El Bendadi; Yissam Lakhdar; El Hassan Sbai

doi:10.1117/12.2268730

17 March 2017 Kernel credal classification rule

Khawla El Bendadi, Yissam Lakhdar, El Hassan Sbai

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 103412I (2017) https://doi.org/10.1117/12.2268730
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

Abstract

In this paper, we propose a kernel version of the credal classification rule (CCR) to perform the classification in a feature space of high dimension. Kernels based approaches have become popular for several years to solve supervised or unsupervised learning problems. In this paper, our method is extended to the CCR. It is realized by replacing the inner product with an appropriate positive definite function, and the corresponding algorithms are called kernel Credal Classification Rule (KCCR). The approach is applied to the classification of the generated and real data to evaluate and compare the performance of the KCCR method with other classification methods.

Citation Download Citation

Khawla El Bendadi, Yissam Lakhdar, and El Hassan Sbai "Kernel credal classification rule", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103412I (17 March 2017); https://doi.org/10.1117/12.2268730

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