CLASSIFICATION DECISION TREE ALGORITHMS IN DATA MINING

Miss.SakshiMahurpawar; Mr. Lowlesh Yadav; Mr. Neehal Jiwane

doi:10.59367/8jekkk81

Authors

Miss.SakshiMahurpawar Department of Computer Science & Engineering, Shri Sai College of Engineering & Technology, Chandrapur, India
Mr. Lowlesh Yadav Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India
Mr. Neehal Jiwane Department of Computer Science and Engineering, Technology, Shri Sai, College Chandrapur, India

DOI:

https://doi.org/10.59367/8jekkk81

Keywords:

Decision Tree Learning, Algorithm, C4.5, Data Minning, ID3

Abstract

As the computer technology and computer network technology are developing, the quantum of data in information assiduity is getting advanced and advanced. It's necessary to dissect this large quantum of data and excerpt useful knowledge from it. Process of rooting the useful knowledge from huge set of deficient, noisy, fuzzy and arbitrary data is called data mining. Decision tree bracket fashion is one of the most popular data mining ways. In decision tree divide and conquer fashion is used as introductory literacy strategy. A decision tree is a structure that includes a root knot, branches, and splint bumps. Each internal knot denotes a test on a trait, each branch denotes the outgrowth of a test, and each splint knot holds a class marker. The topmost knot in the tree is the root knot. This paper focus on the colorful algorithms of Decision tree (ID3, C4.5, wain), their characteristic, challenges, advantage and disadvantage

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