Model for the Prediction of Dropout in Higher Education in Peru applying Machine Learning Algorithms: Random Forest, Decision Tree, Neural Network and Support Vector Machine
University dropout is a problem that not only affects students, but also families, universities, society, and others. This problem has a global character, so it is common to identify it in different parts of the world. However, there are few solutions that efficiently take advantage of available tec...
Main Authors: | Omar A Jimenez, Ashley Jesús Llontop, Lenis Wong |
---|---|
Format: | Article |
Language: | English |
Published: |
FRUCT
2023-05-01
|
Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
Subjects: | |
Online Access: | https://www.fruct.org/publications/volume-33/fruct33/files/Jim.pdf |
Similar Items
-
Web architecture for URL-based phishing detection based on Random Forest, Classification Trees, and Support Vector Machine
by: Julio Lamas Piñeiro, et al.
Published: (2022-05-01) -
Machine Learning Prediction of University Student Dropout: Does Preference Play a Key Role?
by: Marina Segura, et al.
Published: (2022-09-01) -
IoT System for School Dropout Prediction Using Machine Learning Techniques Based on Socioeconomic Data
by: Francisco A. da S. Freitas, et al.
Published: (2020-10-01) -
The Machine Learning-Based Dropout Early Warning System for Improving the Performance of Dropout Prediction
by: Sunbok Lee, et al.
Published: (2019-07-01) -
Predicting metabolic syndrome using decision tree and support vector machine methods
by: Farzaneh Karimi-Alavijeh, et al.
Published: (2016-06-01)