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Employee Turnover Prediction with Machine Learning: A Reliable Approach · Study

WorkEmployee Turnover Prediction with Machine Learning: A Reliable Approach

Yue Zhao2018

Work2018

Employee Turnover Prediction with Machine Learning: A Reliable Approach

Yue Zhao · Maciej K. Hryniewicki · Francesca Cheng · Boyang Fu · Xiaoyu Zhu

170 citations·0/0 files stored·Advances in intelligent systems and computing

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AI and HR Technologies Online Learning and Analytics Customer churn and segmentation

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References

2006Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry 2016Prediction of Employee Turnover in Organizations using Machine Learning Algorithms

Cited by

2021From Big Data to Deep Data to Support People Analytics for Employee Attrition Prediction 2023Responsible artificial intelligence in human resources management: a review of the empirical literature 2022Predictive Model of Employee Attrition Based on Stacking Ensemble Learning 2021On the Applicability of Machine Learning Fairness Notions 2023A decade of research on machine learning techniques for predicting employee turnover: A systematic literature review 2021Machine learning fairness notions: Bridging the gap with real-world applications 2022Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms 2025A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics

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Details

Year2018

Typeother

Published2018-11-07

VenueAdvances in intelligent systems and computing

ISSN-L2194-5357

Languageen

Citations170

Files0 public / 0

ShelfAI and HR Technologies

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doi10.1007/978-3-030-01057-7_56

openalex_workW2900215310

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