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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
http://hdl.handle.net/20.500.12678/0000004360d27492ec-b651-4194-b5d4-a73afa302c1b
cb02edf2-24a1-46bb-a907-d98f09992ea6
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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 |