Applying Data Mining Hybrid Classification Techniques and Decision Tree approach for Government Employee’s Performance Prediction

Computer Engineering

The precious awareness can be revealed through data mining process. In data mining, Taxonomy is one of the key tasks to communicate acquaintance from massive amount of data. Consequently right employee at right position is essential, and is the crate for executing a system using amalgam course of action based on Data Clustering and assessment Tree of Data Mining methods to assist the authority in decision making process for selecting the employee for posting and transfers. This anticipated research work projects how data clustering method can be applied for evaluating the employee recital. Different performance evaluation factors like personality, social sensitivity, efficiency, experience, punctuality, domain assignment of previous postings, ratings of previous work assignment etc. The consequence of the proposed research work predict the number of gov.employees selected for different types of work-assignment and discharged accordance to their performance

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