Generalized Reference Kernel for One-class Classification

• URL: http://arxiv.org/abs/2205.00534v2
• Date: Wed, 4 May 2022 05:40:09 GMT
• Title: Generalized Reference Kernel for One-class Classification
• Authors: Jenni Raitoharju and Alexandros Iosifidis
• Abstract summary: We formulate a new generalized reference kernel to improve the original base kernel using a set of reference vectors. Our analysis and experimental results show that the new formulation provides approaches to regularize, adjust the rank, and incorporate additional information into the kernel itself.
• Score: 100.53532594448048
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we formulate a new generalized reference kernel hoping to improve the original base kernel using a set of reference vectors. Depending on the selected reference vectors, our formulation shows similarities to approximate kernels, random mappings, and Non-linear Projection Trick. Focusing on small-scale one-class classification, our analysis and experimental results show that the new formulation provides approaches to regularize, adjust the rank, and incorporate additional information into the kernel itself, leading to improved one-class classification accuracy.

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