Classified by family issues. The best results are in bold and the second best results are in italics (%).

<p>Classified by family issues. The best results are in bold and the second best results are in italics (%).</p>

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Bibliographic Details
Main Author:	Jianwei Dong (1549075) (author)
Other Authors:	Ruishuang Sun (21567637) (author), Zhipeng Yan (7947353) (author), Meilun Shi (21567640) (author), Xinyu Bi (591554) (author)
Published:	2025
Subjects:	Sociology Science Policy Biological Sciences not elsewhere classified including personal information handle nonlinear relationships gdo ), combined different feature combinations data augmentation techniques also promoted innovation educational data analysis classifying student grades multiple deep learning different machine learning students &# 8217 rbfn model based deep learning models classifying academic performance student performance classification student grades machine learning data sparsity learning outcomes academic performance multiple models educational methods also checked academic achievement work offers variance homogeneity traditional methods poor handling new methods many problems limited ability intervention strategies important index family background f1 score extracurricular activities comprehensive view classification tasks attendance rate accurate prediction 46 %. 12 %,
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