Manuscript Number : SHISRRJ247228

Human Stress Detection Based on Sleeping Habits Using Machine Learning

Authors(2) :-T Muni Kumari, B Pallavi

Emphasise, often known as stressors, is a state of mind or emotions caused on by difficult or inevitable situations. Understanding human stress levels is essential to preventing any negative events in life. Stress is becoming more and more commonplace in human activities, which is bad because it can lead to things like heart attacks, high blood pressure, diabetes, etc. A range of stress levels and sleep patterns, including low, normal, medium, high, and medium low, are included in the dataset that was obtained. After the data had been pre-processed, six machine learning techniques were used in the classification level: Decision trees, Naïve Bayes, Random Forest, Multilayer Perception (MLP), Support Vector Machine (SVM), and Logistic Regression. This allowed for comparison and the most accurate results to be obtained.

Authors and Affiliations

T Muni Kumari
Assistant Professor, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India
B Pallavi
Post Graduate, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India

Random forest Classifier, Stress, Facial Expressions

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Publication Details

Published in : Volume 7 | Issue 2 | March-April 2024
Date of Publication : 2024-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 514-518
Manuscript Number : SHISRRJ247228
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

T Muni Kumari, B Pallavi, "Human Stress Detection Based on Sleeping Habits Using Machine Learning", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 7, Issue 2, pp.514-518, March-April.2024
URL : https://shisrrj.com/SHISRRJ247228

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