International Journal of Commerce and Management Research

author(s)
Shawni Dutta, Samir Kumar Bandyopadhyay

abstract
Any organization or company is strongly aware of the significance of employees in gaining and upholding competitive advantage. While putting concentration on earning maximized profit, employee attrition rates should be considered as an interfering factor. This paper emphasizes on predicting attrition probabilities beforehand by implementing an automated tool. The proposed system implements feed-forward neural network along with 10-fold cross validation procedure under a single platform for predicting employee attrition. This proposed method is evaluated as well as compared with six classifiers such as Support Vector Machine, k-Nearest Neighbor, naïve bayes, Decision Tree, Adaboost, and Random Forest classifiers. Experimental analysis concludes that proposed method outperforms well over aforementioned classifiers in terms of performance measure metrics