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Comparative Analysis of Decision Tree Algorithms

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Nature Inspired Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 652))

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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Author information

Authors and Affiliations

  1. Manav Rachna International University, Faridabad, India

    Mridula Batra & Rashmi Agrawal

Authors
  1. Mridula Batra
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  2. Rashmi Agrawal
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, Delhi, India

    Bijaya Ketan Panigrahi

  2. Bharati Vidyapeeth’s Institute of Computer Applications and Management, New Delhi, Delhi, India

    M. N. Hoda

  3. Department of Computer Science and IT, University of Jammu, Jammu, Jammu and Kashmir, India

    Vinod Sharma

  4. Bharati Vidyapeeth’s Institute of Computer Applications and Management, New Delhi, Delhi, India

    Shivendra Goel

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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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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6746-4

  • Online ISBN: 978-981-10-6747-1

  • eBook Packages: EngineeringEngineering (R0)

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