A Study in Analysing the Factors Influencing Job Satisfaction through Supervised Machine Learning Methods-Reference-Cited by-同舟云学术

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A Study in Analysing the Factors Influencing Job Satisfaction through Supervised Machine Learning Methods

Published:2023-12-07 Issue: Volume:22 Page:1-7
ISSN:
Container-title:2023 1st International Conference on Optimization Techniques for Learning (ICOTL)
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Author:

Venkata Srinivas Akana Chandra Mouli¹,Birajdar Sphurti²,Bethapudi Prakash³,Soujanya K.⁴,Reddy L. Chandra Sekhar⁵,Anusuya M⁶

Affiliation:

1. Bonam Venkata Chalamayya Engineering College,Odalarevu,Andhra Pradesh,India

2. Dr. D.Y. Patil Vidyapeeth,Global Business School and Research Centre,Pune,Maharashtra,India

3. GITAM Deemed to be University,GITAM Institute of Technology,Dept of CSE,Visakhapatnam,Andhra Pradesh,India

4. Koneru Lakshmaiah Education Foundation,Department of BBA,Guntur,Andhra Pradesh,India

5. CMR College of Engineering & Technology, Kandlakoya (v),HOD - CSE(Data Science),Hyderabad,Telangana,India

6. Indra Ganesan College of Engineering,Department of Physics,Trichy,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10434936/10434955/10435218.pdf?arnumber=10435218

Reference20 articles.

1. Burnout, self-efficacy and job satisfaction among primary school teachers in Morocco

2. Teacher and school determinants of teacher job satisfaction: a multilevel analysis

3. Self-reported teaching effectiveness and job satisfaction among teachers: the role of subject matter and other demographic variables

4. Density-Based Unsupervised Learning Algorithm to Categorize College Students into Dropout Risk Levels

5. Machine Learning Based Predictive Model for Risk Assessment of Employee Attrition

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