In any organization’s talent management is becoming an increasingly crucial method of approaching HR functions. Talent management can be defined as an outcome to ensure the right person is in the right job. Human talent prediction is the objective of this study. Due to that reason, classification and prediction in data mining which is commonly used in many areas can also be implemented in this study. There are various classification techniques in data mining such as Decision tree, Neural networks, Genetic algorithms, Support vector machines, Rough set theory, Fuzzy set approach. This research has been made by applying decision tree classification algorithms to the employee’s performance prediction. Decision tree is among the popular classification technique which generates a tree and a set of rules, representing the model of different classes, from a given data set. Some of the decision tree algorithms are ID3, C5.0, Bagging, Random Forest, Rotation forest, CART and CHAID. In this paper give the overview of C4.5 algorithms.

HR Analytics, Talent, Prediction, Decision Tree, Algorithm, C4.5, Classification, Data Mining, Big Data

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