Abstract
Decision trees are outstanding tools to help anyone to select the best course of action. They generate a highly valuable arrangement in which one can place options and study possible outcomes of those options. They also facilitate users to make a fair idea of the pros and cons related to each possible action. A decision tree is used to represent graphically the decisions, the events, and the outcomes related to decisions and events. Events are probabilistic and determined for each outcome. The aim of this paper is to do detailed analysis of decision tree and its variants for determining the best appropriate decision. For this, we will analyze and compare various decision tree algorithms such as ID3, C4.5, CART, and CHAID.
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Batra, M., Agrawal, R. (2018). Comparative Analysis of Decision Tree Algorithms. In: Panigrahi, B., Hoda, M., Sharma, V., Goel, S. (eds) Nature Inspired Computing. Advances in Intelligent Systems and Computing, vol 652. Springer, Singapore. https://doi.org/10.1007/978-981-10-6747-1_4
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DOI: https://doi.org/10.1007/978-981-10-6747-1_4
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