Prediction Model Hadoop-based for High-risk Students

DOI

10.2991/mmsta-19.2019.7How to use a DOI?

Keywords

prediction model; high-risk students; big data; Hadoop platform

Abstract

In order to effectively predict high-risk students, this paper proposed a weighted voting combination prediction model based on Hadoop for high-risk students. Firstly, the design idea of the model was given, and the data of students were stored and processed by Hadoop platform. Secondly, according to the prediction method of students' characteristics and selection, a specific weighted voting combination prediction model Hadoop-based for high-risk students was constructed. Finally, the prediction model was evaluated and the rationality of the model was proved. The model can analyze the collected data of students and predicts the high-risk students in big data environment.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jichao Yu
AU  - Xiaogao Yu
PY  - 2019/12
DA  - 2019/12
TI  - Prediction Model Hadoop-based for High-risk Students
BT  - Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019)
PB  - Atlantis Press
SP  - 30
EP  - 33
SN  - 2352-538X
UR  - https://doi.org/10.2991/mmsta-19.2019.7
DO  - 10.2991/mmsta-19.2019.7
ID  - Yu2019/12
ER  -