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A new fine-grained weighting method in multi-label text classification

Authors
Lee, C.-H.
Issue Date
2014
Publisher
CEUR-WS
Citation
CEUR Workshop Proceedings, v.1144, pp 26 - 30
Pages
5
Indexed
SCOPUS
Journal Title
CEUR Workshop Proceedings
Volume
1144
Start Page
26
End Page
30
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/24658
ISSN
1613-0073
Abstract
Multi-label classification is one of the important research areas in data mining. In this paper, a new multilabel classification method using multinomial naive Bayes is proposed. We use a new fine-grained weighting method for calculating the weights of feature values in multinomial naive Bayes. Our experiments show that the value weighting method could improve the performance of multinomial naive Bayes learning.
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