Interpretable Deep Learning for University Dropout Prediction-Reference-Cited by-同舟云学术

Interpretable Deep Learning for University Dropout Prediction

Published:2020-10-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 21st Annual Conference on Information Technology Education
language:
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Author:

Baranyi Máté¹,Nagy Marcell¹,Molontay Roland²

Affiliation:

1. Budapest University of Technology and Economics, Budapest, Hungary

2. MTA-BME Stochastics Research Group, Budapest, Hungary

Funder

Ministry of Human Capacities

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3368308.3415382

Reference38 articles.

1. Data Mining in Higher Education : University Student Dropout Case Study

2. Deep learning approach for predicting university dropout: a case study at Roma Tre University;Agrusti Francesco;Journal of e-Learning and Knowledge Society,2020

3. Sercan O. Arik and Tomas Pfister. 2019. TabNet: Attentive Interpretable Tabular Learning. arxiv: 1908.07442 [cs.LG] Sercan O. Arik and Tomas Pfister. 2019. TabNet: Attentive Interpretable Tabular Learning. arxiv: 1908.07442 [cs.LG]

4. Analyzing undergraduate students' performance using educational data mining

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