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Ear-sys - an Ensemble Approach Using Super Learner for Employee Attrition Prediction and Retention System

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dc.contributor.author Gamage, Thinayani
dc.date.accessioned 2024-03-13T05:18:56Z
dc.date.available 2024-03-13T05:18:56Z
dc.date.issued 2023
dc.identifier.citation Gamage, Thinayani (2023) Ear-sys - an Ensemble Approach Using Super Learner for Employee Attrition Prediction and Retention System. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2019714
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1875
dc.description.abstract "Employee attrition has become a major concern for organizations, and retaining employees has become crucial for their success. This project proposes an ensemble approach using the Super Learner technique, EAR-Sys, for employee attrition prediction and retention system. This project aims to develop a model that predicts employee attrition with high accuracy and provides insights for retention strategies. This project demonstrates the effectiveness of the Super Learner approach in employee attrition prediction and retention. The findings contribute to the body of knowledge by providing insights into the factors that influence employee attrition and retention. The proposed model has practical implications for HR managers and can help organizations to retain their valuable employees and achieve their strategic goals. " en_US
dc.language.iso en en_US
dc.publisher IIT en_US
dc.subject Employee Attrition en_US
dc.subject Employee Churn en_US
dc.subject Machine Learning en_US
dc.subject Retention Strategies en_US
dc.title Ear-sys - an Ensemble Approach Using Super Learner for Employee Attrition Prediction and Retention System en_US
dc.type Thesis en_US


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