TARNet for the Classification of Time Series with Missing Values: A Strong Baseline
Due to sensor failures and other issues, real-world time series may contain missing values, often in consecutive segments. Classification of such time series is an important task with prominent applications in various domains such as medicine, manufacturing, social networks and environmental sci...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Scientia Publishing House
2024-10-01
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| Series: | Acta Universitatis Sapientiae: Informatica |
| Subjects: | |
| Online Access: | https://acta.sapientia.ro/content/docs/info16-1-01-324608.pdf |
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