Proposing Two Hybrid Data Mining Models for Discovering Students' Mental Health Problems

Proposing Two Hybrid Data Mining Models for Discovering Students' Mental Health Problems

Mental health is an important issue for university students. The objective of this article was to apply and compare the different classification methods for students' mental health problems. Furthermore, it presents an ensemble classification method to improve the accuracy of classifiers and as...

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Bibliographic Details
Main Authors: Shabnam Shadroo, Mohsen Yoosefi Nejad, Samira Tavanaiee Yosefian, Morteza Naserbakht, Mehdi Hosseinzadeh
Format: Article
Language:ces
Published: Prague University of Economics and Business 2021-06-01
Series:Acta Informatica Pragensia
Subjects:
classification
nbtree
adtree
random forest
svm
mental health
majority voting
data mining
Online Access:https://aip.vse.cz/artkey/aip-202101-0006_proposing-two-hybrid-data-mining-models-for-discovering-students-8217-mental-health-problems.php

Internet

https://aip.vse.cz/artkey/aip-202101-0006_proposing-two-hybrid-data-mining-models-for-discovering-students-8217-mental-health-problems.php

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