Why an Employee Leaves: Predicting using Data Mining Techniques

Attri, Tanya (2018) Why an Employee Leaves: Predicting using Data Mining Techniques. Masters thesis, Dublin, National College of Ireland.

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Abstract

HR analyticss is the area of data analyticss helping the organization to understand its employees. Today companies face employee attrition as the major issue effecting the productive functioning of the organization. HR analyticss has enhanced the area of data analytics to an extent that organizations can figure out their employees' characteristics; where inaccuracy leads to incorrect decision making. Data mining is helping the HR department with methods to evaluate the historical data and predict the employee attrition, the baseline for this research. By far, employee attrition is predicted with the suggestions of the domain experts and the use of the classification methods by technical researchers. This research aims to investigate the extent to which ML techniques can help in predicting the employees who might leave, using the optimal hybrid ML models, where oversampling technique (SMOTE) & feature selection technique (SA) are integrated with the classication algorithms such as SVM & LR. The focus is towards the true positive accuracy predicted by the models. A comparison of these results was done between the features selected by the models in this research and the ones listed by the domain expert researchers in the past to see which one has the more reliable outcomes, concluding that the management expert should use the technical methods for their analysis in future to have reliable outcomes. This will help the HR system to adopt the right scenarios in real time & correctly predict the potential employees to leave & know why they do so.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Human Resource Management H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Talent Management
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Caoimhe Ní Mhaicín
Date Deposited:	06 Nov 2018 09:56
Last Modified:	06 Nov 2018 09:56
URI:	https://norma.ncirl.ie/id/eprint/3434

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