An Analysing Employee Attrition Using Machine Learning

Technology has brought in revolutionary changes in the business processes of organizations with technologies like Big Data Analytics, Artificial Intelligence and Robotics. Predictive analytics is one such innovative technology which is widely used by organizations. With the advent of computers in all areas of work, organizations possess massive amounts of data in structured and unstructured forms. An analysis of these data by using technology like data mining paves way for predicting future trends and behavior, which in turn results in more data driven decision making. These predictions can be made in various functional areas of an organization. The rationale of this study is to use data mining techniques to understand the factors influencing attrition of human resources using Weka. Weka is a data science tool that can be used for predictive analytics. In knowledge-based organizations, attrition is a severe apprehension because it affects the competitive strength of business. Weka can be employed to cluster data with techniques like k-means algorithm to explain the factors leading to attrition. A comparison of algorithms in Weka can also be made to understand the effectiveness. The dataset provided by IBM is used for this study