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Comparison of Data Mining Classification Algorithms, C5.0 and CART for Car Evaluation and Credit Card Information Datasets

http://hdl.handle.net/20.500.12678/0000004360
d27492ec-b651-4194-b5d4-a73afa302c1b
cb02edf2-24a1-46bb-a907-d98f09992ea6
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NJPSC NJPSC 2019 Proceedings-pages-75-80.pdf (374 Kb)
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Article
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Publication
Title
Title Comparison of Data Mining Classification Algorithms, C5.0 and CART for Car Evaluation and Credit Card Information Datasets
Language en_US
Publication date 2019-03
Authors
Maung, Ei Thinzar Win
Aye, Zin May
Description
Data mining is the use of algorithm to discoverenormous amount of data automatically by searchinghidden information from large data sets usingmultiple algorithms and techniques. Differentmethods and algorithms are available in data miningsystem. Classification and prediction are the mostcommon method used to make out models and predictprobable data patterns and can be solving severalproblems in different domains like education,medicine, business, and science. In the presentscenario, as almost everything is becomingcomputerized, various classifications algorithms havebeen developed to make the automatic decisionprocess. The Decision Tree is an imperativeclassification method in data mining classification.This paper provides a comparison between two datamining classification algorithms: C5.0 and CART(classification and regression tree) applied on twodifferent UCI datasets: car evaluation dataset andcredit card dataset.
Keywords
data mining, classification, decision tree, C5.0, CART
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/2299
Journal articles
National Journal of Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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