Mental State Prediction of College Students Based on Decision Tree

Qixin Bo () and Xuedong Gao ()
Additional contact information
Qixin Bo: University of Science and Technology Beijing
Xuedong Gao: University of Science and Technology Beijing

A chapter in LISS 2021, 2022, pp 345-357 from Springer

Abstract: Abstract Based on the relevant data of college students’ mental health status and various social problems caused by it, this paper constructs a prediction model of college students’ mental health by using decision tree C4.5 algorithm, and extracts classification rules to predict and evaluate the mental health status of college students. The experimental results show that the model has a good accuracy and can correctly classify the mental health status of college students. To some extent, the prediction model can provide reference for the planning and decision-making of mental health education in colleges and universities.

Keywords: Data mining; Decision tree; C4.5 algorithm; Mental health (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-16-8656-6_32

Ordering information: This item can be ordered from
http://www.springer.com/9789811686566

DOI: 10.1007/978-981-16-8656-6_32

Access Statistics for this chapter

More chapters in Lecture Notes in Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().