Multi-Class, Multi-Label and Multi-Target in Wineinformatics

Author:

Chen Bernard

Publisher

Springer Nature Singapore

Reference12 articles.

1. Spyromitros-Xioufis, E., Groves, W., Tsoumakas, G., Vlahavas, I.: Multi-label classification methods for multi-target regression. arXiv, 1211.6581v1 (2012)

2. Anderson, K.: The World’s Wine Markets: Globalization at Work. Edward Elgar, Cheltenham (2004)

3. Tawiah, C.A., Sheng, V.S.: Empirical comparison of multi-label classification algorithms. In: Proc. 27th AAAI Conf. on Artificial Intelligence, Bellevue, WA, USA, pp. 2–6. AAAI, Menlo Park, CA (2013)

4. Tsoumakas, G., Katakis, I.: Multi-label classification: an overview. In: Erickson, J. (ed.) Database Technologies: Concepts, Methodologies, Tools, and Applications, pp. 4–6. IGI Global, Barcelona (2009) 10–12

5. Zhang, M.-L., Li, Y.-K., Liu, X.-Y., Geng, X.: Binary relevance for multi-label learning: an overview. Front. Comput. Sci. 12(2), 191–202 (2018)

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