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 [1].
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Notes
- 1.
Available at http://www.tsv.fi/julkaisufoorumi/haku.php.
- 2.
Available at http://www.juuli.fi/?&lng=en.
- 3.
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Akusok, A., Saarela, M., Kärkkäinen, T., Björk, KM., Lendasse, A. (2019). Mislabel Detection of Finnish Publication Ranks. In: Cao, J., Vong, C., Miche, Y., Lendasse, A. (eds) Proceedings of ELM-2017. ELM 2017. Proceedings in Adaptation, Learning and Optimization, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-01520-6_22
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DOI: https://doi.org/10.1007/978-3-030-01520-6_22
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