A CLASSIFICATION AND DECISION TREE IS A KEY APPROACHES TO DATA MINING

Abstract

Classification and Decision Tree is one of the most important data mining approaches for improved the performance. Apply the complete approaches to a large data then helps to make use of its measurements more competently to enhance the data mining capability. We elaborate a practical and formal Classification and Decision Tree that enables security assessment using fault design factors. The Classification and Decision Tree approaches are more practicable for Data mining terminology and protection inexpensively. This paper proposes a Classification and Decision Tree approaches for data mining. The proposed evaluation for data Ming approaches point outs the possible influence of techniques properties and also talk about the impact of computation with various factors.