One-Class Classification Using ℓp-Norm Multiple Kernel Fisher Null Approach

We address the one-class classification (OCC) problem and advocate a one-class MKL (multiple kernel learning) approach for this purpose. To this aim, based on the Fisher null-space OCC principle, we present a multiple kernel learning algorithm where an ℓ p -norm regularisation ( p ≥ 1) is considered...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 32; p. 1
Main Author:	Arashloo, Shervin Rahimzadeh
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Classification Kernel Kernels Machine learning multiple kernel learning One-class classification one-class Fisher null transformation Optimization Pattern recognition Regularization Saddle points Search problems Support vector machines Task analysis Training ℓ<sub xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> p -norm regularisation
ISSN:	1057-7149, 1941-0042, 1941-0042
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!