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Predicting Employees Performance using Data Mining Techniques

Samruddhi Gavas, Darshan Oswal, Ronish Rathod, Madhu Nashipudimath

Abstract


Human resources management (HRM) has become one of the essential interests of managers and 4decision-makers in almost all types of businesses to adopt plans for correctly discovering highly qualified employees. In this research, data mining techniques were utilized to build a classification model for predicting the performance of employees using a real dataset. For this, we are using different methods such as support vector machine, Logistic Regression and Neural Network. This System rates the performance of employees and gives a predictive analysis of data mining techniques. Our main objective is how the training/test split ratio affects the estimation of the generalization performance and to find the best algorithm for predicting employee performance.


Keywords


Neural network, logistic regression, SVM, classification, data mining, employees performance rating, data splitting

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