An Improved Self-Training Method for Positive Unlabeled Time Series Classification Using DTW Barycenter Averaging

Traditional supervised time series classification (TSC) tasks assume that all training data are labeled. However, in practice, manually labelling all unlabeled data could be very time-consuming and often requires the participation of skilled domain experts. In this paper, we concern with the positiv...

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Detalles Bibliográficos
Autores principales: Li, Jing, Zhang, Haowen, Dong, Yabo, Zuo, Tongbin, Xu, Duanqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587877/
https://www.ncbi.nlm.nih.gov/pubmed/34770721
http://dx.doi.org/10.3390/s21217414

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587877/
https://www.ncbi.nlm.nih.gov/pubmed/34770721
http://dx.doi.org/10.3390/s21217414

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