Study and Analysis of Decision Tree Based Classification Algorithms

Authors

  • Patel HH Dept. of Information Technology, CSPIT, Charotar University of Science and Technology, Changa, Gujarat, India
  • Prajapati P Dept. of Information Technology, CSPIT, Charotar University of Science and Technology, Changa, Gujarat, India

Keywords:

Machine Learning, Decision Tree (DT), WEKA tool

Abstract

Machine learning is to learn machine on the basis of various training and testing data and determines the results in every condition without explicit programmed. One of the techniques of machine learning is Decision Tree. Different fields used Decision Tree algorithms and used it in their respective application. These algorithms can be used as to find data in replacement statistical procedures, to extract text, medical certified fields and also in search engines. Different Decision tree algorithms have been built according to their accuracy and cost of effectiveness. To use the best algorithm in every situations of decision making is very important for us to know. This paper includes three different algorithms of Decision Tree which are ID3, C4.5 and CART

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Published

2025-11-17

How to Cite

[1]
H. H. Patel and P. Prajapati, “Study and Analysis of Decision Tree Based Classification Algorithms”, Int. J. Comp. Sci. Eng., vol. 6, no. 10, pp. 74–78, Nov. 2025.

Issue

Vol. 6 No. 10 (2018): IJCSE October Edition

Section

Research Article

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