Exploring Active Learning for Student Behavior Classification

Exploring Active Learning for Student Behavior Classification

Selection of high-quality ground truth data is a critical step for machine learning. Conventionally, a human-centered strategy is utilized to label the data. While this technique provides accurate annotations of task-specific behaviors, it is difficult, costly and error-prone. One method explored to...

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Main Authors:	Dumdumaya, Cristina E, Paredes, Yance Vance M, Rodrigo, Ma. Mercedes T
格式:	text
出版:	Archīum Ateneo 2019
主題:	Computing methodologies Machine learning Learning settings Active learning settings Computer Sciences
在線閱讀:	https://archium.ateneo.edu/discs-faculty-pubs/164 https://dl.acm.org/doi/abs/10.1145/3323771.3323807
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