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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM25692

Stress Level Prediction of College Students Using ML

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM25692

Volume:

7 |

9 |

Sep 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AD

Akash D

PR

Pushpalatha R

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Abstract

College students’ mental health is often neglected, which may have serious consequences for their success in academic records. Mental health issues among college students may have far-reaching consequences for both the campus and the students themselves. General counselling, student management systems, and human advisers are just some of the ineffective approaches that institutions are using to track and avoid student stress. Naive Bayes, K-Nearest Neighbor, and Decision Tree are just a few examples of the Machine Learning Algorithms used by the proposed system to determine whether or not a student is experiencing stress and, if student is in stress, the system provide solution for relieving that stress.

KEYWORDS

Machine Learning Naïve Bayes K-Nearest Neighbor Decision Tree Stress Stress Free Prediction

Cite This Article

Akash D, Pushpalatha R, "Stress Level Prediction of College Students Using ML," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 9, Sep 2023. https://doi.org/10.55041/IJSREM25692

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Publication Date

9/14/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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