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Survey Paper | Computer Science & Engineering | India | Volume 5 Issue 4, April 2016
A Survey on Decision Tree Algorithms of Classification in Data Mining
Himani Sharma | Sunil Kumar [64]
Abstract: As the computer technology and computer network technology are developing, the amount of data in information industry getting higher and higher. It is necessary to analyse this large amount of data and extract useful knowledge from it. Process of extracting the useful knowledge from huge set of incomplete, noisy, fuzzy and random data is called data mining. Decision tree classification technique is one of the most popular data mining technique. In decision tree divide and conquer technique is used as basic learning strategy. A decision tree is a structure that includes a root node, branches, and leaf nodes. Each internal node denotes a test on an attribut, each branch denotes the outcome of a test, and each leaf node holds a class label. The topmost node in the tree is the root node. This paper focus on the various algorithms of Decision tree (ID3, C4.5, CART), their characteristic, challenges, advantage and disadvantage.
Keywords: Decision Tree Learning, classification, C45, CART, ID3
Edition: Volume 5 Issue 4, April 2016,
Pages: 2094 - 2097
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Experimental Result Paper, Computer Science & Engineering, India, Volume 11 Issue 6, June 2022
Pages: 1038 - 1041Classification of Glassdoor Pros and Cons into Pre-Defined Categories
Mahak [9] | Aditya Raj Gupta [2] | Deepti Buriya
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Survey Paper, Computer Science & Engineering, India, Volume 11 Issue 7, July 2022
Pages: 1023 - 1029A Survey and High-Level Design on Human Activity Recognition
Abhishikat Kumar Soni | Dhruv Agrawal | Md. Ahmed Ali | Dr. B. G. Prasad [4]