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Accuracy vs. Cost in Decision Trees: A Survey

机译:决策树中准确性与成本的关系:一项调查

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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.
机译:决策树已广泛应用于金融,营销,工程和医学等许多领域的分类。越来越多的应用领域要求深入理解决策树的各个方面。另外,至关重要的是要了解决策树分类器中与分类任务相关的不同类型的费用,以及它们与分类器准确性之间的关系,因为平衡这两者是当今许多领域(例如医学诊断)的主要关注点。本文介绍了决策树的概念,介绍了决策树在数据挖掘中的各种应用领域,总结了标准决策树算法,并指出了它们的主要优缺点。它的主要目的是弄清决策树中分类准确性和分类成本之间的关系。

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