利用机器学习和集成学习设想和保留大学劳动力流失

Avinash L. Golande, Vasudev Surwase, Neha Patil, Janhvi Bhandekar, Jay Shinde
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引用次数: 0

摘要

本研究的目的是在情境中确定大学劳动力的流失,以找到大学的流失。员工流失是指员工因任何原因离职。在许多组织中,在指定的教育学院或大学中,都面临着人员流失的问题。员工减员是指员工数量的逐渐减少。在人员流失的情况下,在合适的地点和时间找到具有合适才能的合适人选,对一个组织来说是代价高昂的。由于人员流失,员工的生活不稳定。我们专注于找出哪些员工对组织有益,以及他为什么要使用ML模型和集成模型离开组织。我们专注于通过问卷调查创建我们的学院数据集。造成员工流失的两个主要因素是“工作满意度和薪水”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Envisaging and Retaining College Workforce Attrition using Machine Learning and Ensemble Learning
The aim of this study is to identify attrition of college workforce in a contextual manner to find attrition for the college. Attrition occurs when an employee leaves a job for any reason. The attrition factor is faced in many organizations, in nominated educational colleges, or universities. Attrition is gradual reduction in number of employees. Finding the right individuals with the correct talents employed at the right location and time can be costly for an organization in the event of attrition. Due to attrition, employees create instability in their lives. We focus on finding out which employee is beneficial to the organization and why he is leaving the organization using ML models, and ensemble models. We focus on creating our dataset of the college by taking a questionnaire survey. The two main factors that are responsible for attrition are “job satisfaction and salary”.
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