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Classification on grade, price, and region with multi-label and multi-target methods in wineinformatics
- Source :
- Big Data Mining and Analytics. 3:1-12
- Publication Year :
- 2020
- Publisher :
- Tsinghua University Press, 2020.
-
Abstract
- Classifying wine according to their grade, price, and region of origin is a multi-label and multi-target problem in wine-informatics. Using wine reviews as the attributes, we compare several different multi-label/multitarget 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.
- Subjects :
- Wine
Computer Networks and Communications
business.industry
Computer science
Region of origin
Machine learning
computer.software_genre
Computer Science Applications
Support vector machine
ComputingMethodologies_PATTERNRECOGNITION
Multi target
Artificial Intelligence
Informatics
Artificial intelligence
business
computer
Information Systems
Subjects
Details
- ISSN :
- 20960654
- Volume :
- 3
- Database :
- OpenAIRE
- Journal :
- Big Data Mining and Analytics
- Accession number :
- edsair.doi...........b4591c8ded925bcb9cd5fb1d889fb513
- Full Text :
- https://doi.org/10.26599/bdma.2019.9020014