Accuracy vs. Cost in Decision Trees: A Survey

Abstract

Decision Trees have been applied widely for classification in many fields such as finance, marketing, engineering, and medicine. The increased field of application, made the requirement for understanding various aspects of decision trees in deep. In addition, it is crucial to understand the different type of costs associated with the classification task in a decision tree classifier and their relationship with the classifier’s accuracy, as balancing the two is a major concern these days in many fields such as medical diagnosis. This paper introduces the concept of decision trees, presents their various areas of application in data mining, summarizes the standard decision tree algorithms, and identifies their main advantages and disadvantages. It mainly aims to clarify relationship between the classification accuracy and classification cost in decision trees.