EMPLOYEE PERFORMANCE EVALUATION USING MACHINE LEARNING ALGORITHM
The main objective is to provide the performance appraisal report of an employee using Decision Tree algorithm. The data mining classification methods like decision tree, rule mining, clustering etc. can be applied for evaluating the employee data for giving promotion, yearly increment and career advancement. In order to provide yearly increment for an employee, the historical data stored in the table are subjected to learning by using the decision tree algorithm and the performance are found by testing the attributes of an employee against the rules generated by the decision tree classifier. This paper concentrates on collecting data about employees using the user interface, generating a decision tree from the historical data, testing the decision tree with attributes of an employee and generating the output as whether to give the promotion or not. The information of the user is compared with the trained data stored in the decision tree. The final goal node is to determine whether the employee will get yearly increment, promotion or not.
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