ANALYSIS OF DECISION TREE ALGORITHM IN MACHINE LEARNING

ELECTRICAL ENGINEERING

Machine learning is the ability to improve the behavior with experience. It is about building computer systems that automatically improve the experience. To make out important classes and predict likely pattern, classification and prediction are most important strategies. In data mining decision tree algorithm is an important classification techniques. As the traditional algorithm of decision tree such as Iterative dichotomiser 3 ,C4.5 and C5.0 has the prosperity of tremendous prediction or classification speed, powerful learning volume and easy to build. However for realistic application these techniques are inadequate. Decision tree techniques are mainly used in E-commerce, social network, web search, and space exploration applications. This paper gives the point of different decision tree technologies such as characteristics, difficulties, preferred standpoint and weakness.

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