UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 3
March-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRFV06012


Registration ID:
510503

Page Number

54-58

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Title

STRESS DETECTION USING MACHINE LEARNING TECHNIQUES

Abstract

In this paper we can detect the stress by using the machine learning algorithm. Nowadays, stress is a major problem for many youngsters. The time period that was formerly thought to be the most carefree is currently under a lot of stress. The stress increased a wide variety of problems such as depression, suicide, heart attack, and stroke. The body's natural response to change is a series of physical, emotional, and intellectual responses. Three classification algorithms, logistic regression, random forest, and the decision tree algorithm are applied. The stress dataset was downloaded from Kaggle. By comparing three algorithms, Random forest gives the best accuracy.

Key Words

Classification, Stress, Machine learning,Depression,Suicide.

Cite This Article

"STRESS DETECTION USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.54-58, March-2023, Available :http://www.jetir.org/papers/JETIRFV06012.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"STRESS DETECTION USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. pp54-58, March-2023, Available at : http://www.jetir.org/papers/JETIRFV06012.pdf

Publication Details

Published Paper ID: JETIRFV06012
Registration ID: 510503
Published In: Volume 10 | Issue 3 | Year March-2023
DOI (Digital Object Identifier):
Page No: 54-58
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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