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Reseach Article

Machine Learning on Emotional Intelligence and Work Life Balance

by P. Julia Grace, N. Nasreen Banu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 10
Year of Publication: 2015
Authors: P. Julia Grace, N. Nasreen Banu
10.5120/20376-2597

P. Julia Grace, N. Nasreen Banu . Machine Learning on Emotional Intelligence and Work Life Balance. International Journal of Computer Applications. 116, 10 ( April 2015), 36-39. DOI=10.5120/20376-2597

@article{ 10.5120/20376-2597,
author = { P. Julia Grace, N. Nasreen Banu },
title = { Machine Learning on Emotional Intelligence and Work Life Balance },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 10 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 36-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number10/20376-2597/ },
doi = { 10.5120/20376-2597 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:56:46.705668+05:30
%A P. Julia Grace
%A N. Nasreen Banu
%T Machine Learning on Emotional Intelligence and Work Life Balance
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 10
%P 36-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Emotions are an essential part of our biological makeup, and every morning they march into the office with us and influence our behavior. Our ultimate focus is on Emotional Intelligence (EI) and we combine with data mining technology. Dealing with employees emotions using different machine learning techniques is one of the phenomenal researches in today's world. Here, we examine how far the employees are conscious of their own self and found the ideas and views of an individual about themselves and others. Without proper knowledge about their personality it will be very difficult for an individual to manage their own emotions. This study aims at finding out the individual abilities to manage their emotions in order to perform well. The clustering and classification techniques are applied on same dataset of human emotions, which deals with different types of analysis.

References
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  7. P. Julia Grace and Suman Sharma, "An analytical approach on Chennai road accidents-Machine Learning approach", IJSC, March 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Emotional intelligence Stress Job satisfactions and Productivity