Mislabel Detection of Finnish Publication Ranks
Abstract
The paper proposes to analyze a data set of Finnish ranks of academic publication channels with Extreme Learning Machine (ELM). The purpose is to introduce and test recently proposed ELM-based mislabel detection approach with a rich set of features characterizing a publication channel. We will compare the architecture, accuracy, and, especially, the set of detected mislabels of the ELM-based approach to the corresponding reference results in.
Main Authors
Format
Conferences
Conference paper
Published
2019
Series
Subjects
Publication in research information system
Publisher
Springer International Publishing
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201810234499Käytä tätä linkitykseen.
Parent publication ISBN
978-3-030-01519-0
Review status
Peer reviewed
ISSN
2363-6084
DOI
https://doi.org/10.1007/978-3-030-01520-6_22
Conference
International Conference on Extreme Learning Machine
Language
English
Published in
Proceedings in Adaptation, Learning and Optimization
Is part of publication
Proceedings of ELM-2017
Citation
- Akusok, A., Saarela, M., Kärkkäinen, T., Björk, K.-M., & Lendasse, A. (2019). Mislabel Detection of Finnish Publication Ranks. In J. Cao, C. M. Vong, Y. Miche, & A. Lendasse (Eds.), Proceedings of ELM-2017 (pp. 240-248). Springer International Publishing. Proceedings in Adaptation, Learning and Optimization, 10. https://doi.org/10.1007/978-3-030-01520-6_22
License
Copyright© Springer Nature Switzerland AG 2019