Classification on Grade, Price, and Region with Multi-Label and Multi-Target Methods in Wineinformatics
Classifying wine according to their grade, price, and region of origin is a multi-label and multi-target problem in wineinformatics. Using wine reviews as the attributes, we compare several different multi-label/multi-target methods to the single-label method where each label is treated independentl...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2020-03-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2019.9020014 |
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| Summary: | Classifying wine according to their grade, price, and region of origin is a multi-label and multi-target problem in wineinformatics. Using wine reviews as the attributes, we compare several different multi-label/multi-target methods to the single-label method where each label is treated independently. We explore both single-label and multi-label approaches for a two-class problem for each of the labels and we explore both single-label and multi-target approaches for a four-class problem on two of the three labels, with the third label remaining a two-class problem. In terms of per-label accuracy, the single-label method has the best performance, although some multi-label methods approach the performance of single-label. However, multi-label/multi-target metrics approaches do exceed the performance of the single-label method. |
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| ISSN: | 2096-0654 |