Data mining classification technique for talent management using SVM

In Human Resource Management (HRM), the top challenge for HR professionals is managing the organizational talents. The talent management problem can be solved using the classification technique in data mining. There are several classification techniques present such as Decision Tree, Neural Networks, Support vector machine (SVM) and nearest neighbour algorithm. In this paper we suggest a combined hybrid approach CACC-SVM for potential classification of HR data. This approach yields better accuracy than the traditional classification algorithms because of concise summarization of continuous attributes through CACC discretization and high performing generalized classifier SVM.