A Comparison of Animal Type Classification Efficiency using Data Mining Techniques

Please use this identifier to cite or link to this item: https://publication.npru.ac.th/jspui/handle/123456789/809

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DC Field	Value	Language
dc.contributor.author	Lukkananuruk, Nitima	-
dc.contributor.author	Maneesuk, Jarukit	-
dc.contributor.author	Hoonthong, Wipawadee	-
dc.contributor.author	Hengpraphorm, Kairung	-
dc.contributor.author	Hengpraphorm, Supojn	-
dc.date.accessioned	2020-10-12T07:21:43Z	-
dc.date.available	2020-10-12T07:21:43Z	-
dc.date.issued	2020-07-10	-
dc.identifier.uri	https://publication.npru.ac.th/jspui/handle/123456789/809	-
dc.description.abstract	The aim of this research is to compare the efficiency of appropriate with the animal classification techniques. Two data classification techniques: JRIP and Decision Tree (J48) are used to find the efficiency of animal classification. The experimental results show that Decision Tree (J48) provides the best classification accuracy for animal data (the accuracy of data classification = 97.08%). The second technique is JRIP which provides the accuracy of data classification = 87.13% respectively.	en_US
dc.subject	Classification	en_US
dc.subject	Decision Tress	en_US
dc.subject	J48	en_US
dc.subject	JRIP	en_US
dc.title	A Comparison of Animal Type Classification Efficiency using Data Mining Techniques	en_US
Appears in Collections:	Proceedings of the 12th NPRU National Academic Conference

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