Employee attrition prediction using ensemble learning algorithms
- سال انتشار: 1399
- محل انتشار: هفدهمین کنفرانس بین المللی مهندسی صنایع
- کد COI اختصاصی: IIEC17_033
- زبان مقاله: انگلیسی
- تعداد مشاهده: 513
نویسندگان
MSc Student in Industrial Engineering, Deep Learning Research Lab, Department of Computer Engineering, Faculty of Engineering, College of Farabi, University of Tehran, Iran
Assistant Professor, Deep Learning Research Lab, Department of Computer Engineering, Faculty of Engineering, College of Farabi, University of Tehran, Iran
چکیده
Nowadays, due to various costs following the attrition of employees and the hiring of new people, managers prefer to have loyal employees in their company. On the other hand, the existence of a vast amount of data in the human resources departments has made it impossible for managers to analyze this information with traditional methods to make decisions. Data mining techniques using machine learning algorithms are new methods that can provide meaningful patterns and useful analyzes of a large amount of data in a short period of time. This study aims to create a predictive model for employee attrition using data mining techniques and machine learning algorithms. Based on this, company managers will be able to use this model to make smart decisions to retain current valuable employees and hire loyal employees in the future. Ensemble learning algorithms that combine several individual methods, usually considering each method's strengths and eaknesses, can provide better performance than the individual models separately. As a result of this work, the voting method, which is one of the ensemble learning models, had the highest accuracy of prediction, which was 92%.کلیدواژه ها
employee's attrition, human resource management, data mining, machine learning, ensemble algorithmsمقالات مرتبط جدید
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اطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.