Solving the Imbalanced and Limited Data Labeled for Automated Essay Scoring using Cost Sensitive XGBoost and Pseudo-Labeling
There are two main problems on forming the Automatic Essay Scoring Model. They are the datasets having imbalanced amount of the right and wrong answers and the minimal use of labeled data in the model training. The model forming based on these problems is divided into three main points, namely...
| Main Authors: | , |
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| Format: | Other |
| Language: | English |
| Published: |
International Journal of Advanced Computer Science and Applications
2022
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| Online Access: | https://repository.ugm.ac.id/284295/1/Solving-the-Imbalanced-and-Limited-Data-Labeled-for-Automated-Essay-Scoring-using-Cost-Sensitive-XGBoost-and-PseudoLabelingInternational-Journal-of-Advanced-Computer-Science-and-Applications.pdf |