Evaluation of Machine Learning Models for Employee Churn Prediction

Abstract

The aim of this paper is to study a new prediction method for the churn problem in Information Technology Sectors. For this end, a logistic regression model is built, which integrates a machine learning algorithm logistic regression model from statistics and data analytics. First, we have to classify churn and non-churn employees utilizing the logistic regression model to, and then the organisation can do the needful to retain them. At last, we present the outcomes of a simulative assessment and prove that the presented method is conducive to analysing the churn problem in human resource analytics.