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Who’s Next: Evaluating Attrition with Machine Learning Algorithms and Survival Analysis · Study

WorkWho’s Next: Evaluating Attrition with Machine Learning Algorithms and Survival Analysis

Jessica Frierson2018

Work2018

Who’s Next: Evaluating Attrition with Machine Learning Algorithms and Survival Analysis

Jessica Frierson · Dong Si

19 citations·0/0 files stored·Lecture notes in computer science

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

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References

2016Prediction of Employee Turnover in Organizations using Machine Learning Algorithms 2010Employee churn prediction 2012An Analytics Approach for Proactively Combating Voluntary Attrition of Employees 2009Employee turnover: a novel prediction solution with effective feature selection

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2021Uplift modeling VS conventional predictive model: A reliable machine learning model to solve employee turnover 2019An Explicative and Predictive Study of Employee Attrition Using Tree-based Models

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2020Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programmingarticle · 2 shared references 2018Predicting Employee Attrition using Machine Learningother · 2 shared references 2017Evaluation of machine learning models for employee churn predictionother · 2 shared references 2018Predicting Employee Attrition using XGBoost Machine Learning Approachother · 2 shared references 2020A novel scheme for employee churn problem using multi-attribute decision making approach and machine learningarticle · 2 shared references 2023A decade of research on machine learning techniques for predicting employee turnover: A systematic literature reviewreview · 2 shared references

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Year2018

Typeother

Published2018-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations19

Files0 public / 0

ShelfAI and HR Technologies

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doi10.1007/978-3-319-94301-5_19

openalex_workW2809290620

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