A4 Article in conference proceedings
Linear-Time One-Class Classification with Repeated Element-Wise Folding (2024)
Raitoharju, J. (2024). Linear-Time One-Class Classification with Repeated Element-Wise Folding. In 32nd European Signal Processing Conference (EUSIPCO 2024) : Proceedings (pp. 1952-1956). IEEE. European Signal Processing Conference. https://doi.org/10.23919/eusipco63174.2024.10715412
JYU authors or editors
Publication details
All authors or editors: Raitoharju, Jenni
Parent publication: 32nd European Signal Processing Conference (EUSIPCO 2024) : Proceedings
Place and date of conference: Lyon, France, 26.-30.8.2024
ISBN: 979-8-3315-1977-3
eISBN: 978-9-4645-9361-7
Journal or series: European Signal Processing Conference
ISSN: 2219-5491
eISSN: 2076-1465
Publication year: 2024
Publication date: 26/08/2024
Pages range: 1952-1956
Number of pages in the book: 2761
Publisher: IEEE
Publication country: United States
Publication language: English
DOI: https://doi.org/10.23919/eusipco63174.2024.10715412
Publication open access: Not open
Publication channel open access:
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/99074
Web address of parallel published publication (pre-print): https://arxiv.org/abs/2408.11412
Abstract
This paper proposes an easy-to-use method for one-class classification: Repeated Element-wise Folding (REF). The algorithm consists of repeatedly standardizing and applying an element-wise folding operation on the one-class training data. Equivalent mappings are performed on unknown test items and the classification prediction is based on the item's distance to the origin of the final distribution. As all the included operations have linear time complexity, the proposed algorithm provides a linear-time alternative for the commonly used computationally much more demanding approaches. Furthermore, REF can avoid the challenges of hyperparameter setting in one-class classification by providing robust default settings. The experiments show that the proposed method can produce similar classification performance or even outperform the more complex algorithms on various benchmark datasets. Matlab codes for REF are publicly available at https://github.com/JenniRaitoharju/REF.
Keywords: classification; algorithms; machine learning
Free keywords: One-class Classification; Linear-time; Repeated Element-wise Folding
Contributing organizations
Ministry reporting: Yes
VIRTA submission year: 2024
Preliminary JUFO rating: 1