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Predicting Student Performance in Distance Higher Education Using Active Learning.

, , , and . EANN, volume 744 of Communications in Computer and Information Science, page 75-86. Springer, (2017)

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Evaluating Active Learning Methods for Bankruptcy Prediction., , , and . BFAL, volume 10512 of Lecture Notes in Computer Science, page 57-66. Springer, (2017)Early dropout prediction in distance higher education using active learning., , , and . IISA, page 1-6. IEEE, (2017)Ανάπτυξη πρωτότυπων αλγορίθμων μηχανικής μάθησης για χρήση σε εκπαιδευτικά δεδομένα και σε συστήματα διαχείρισης εκπαιδευτικού περιεχομένου. University of Patras, Greece, (2020)National Archive of PhD Theses: oai:10442/47275.Fuzzy-based active learning for predicting student academic performance using autoML: a step-wise approach., , , and . J. Comput. High. Educ., 33 (3): 635-667 (2021)Predicting Student Performance in Distance Higher Education Using Semi-supervised Techniques., , and . MEDI, volume 9344 of Lecture Notes in Computer Science, page 259-270. Springer, (2015)Using Active Learning Methods for Predicting Fraudulent Financial Statements., , , and . EANN, volume 744 of Communications in Computer and Information Science, page 351-362. Springer, (2017)A Soft-Voting Ensemble Based Co-Training Scheme Using Static Selection for Binary Classification Problems., , and . Algorithms, 13 (1): 26 (2020)Multiview Learning for Early Prognosis of Academic Performance: A Case Study., , and . IEEE Trans. Learn. Technol., 12 (2): 212-224 (2019)Semi-supervised regression: A recent review., , , and . J. Intell. Fuzzy Syst., 35 (2): 1483-1500 (2018)CST-Voting: A semi-supervised ensemble method for classification problems., , , and . J. Intell. Fuzzy Syst., 35 (1): 99-109 (2018)