Please use this identifier to cite or link to this item: https://publication.npru.ac.th/jspui/handle/123456789/1936
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dc.contributor.authorSuksamai, Chutima-
dc.contributor.authorKairung Hengpraprohm, Kairung-
dc.contributor.authorHengpraprohm, Supojn-
dc.date.accessioned2023-11-06T10:13:38Z-
dc.date.available2023-11-06T10:13:38Z-
dc.date.issued2023-07-14-
dc.identifier.isbn978-974-7063-43-1-
dc.identifier.urihttps://publication.npru.ac.th/jspui/handle/123456789/1936-
dc.description.abstractThe objectives of this research are: 1) to study the methods for data classification of hepatitis virus occurrence, and 2) to compare the efficiency of hepatitis data classification by using 3 techniques including k Nearest Neighbor, Decision Tree, and Naive Bayes. The results show Naive Bayes and the Decision Tree give the best performance by providing 100% accuracy, 100% accuracy, and 100% recall followed by k Nearest neighbor with 91% accuracy, 91% accuracy, and 100% recall.en_US
dc.publisherThe 15th NPRU National Academic Conference Nakhon Pathom Rajabhat Universityen_US
dc.relation.ispartofseriesProceedings of the 15th NPRU National Academic Conference;613-
dc.subjectK-Nearest neighboren_US
dc.subjectDecision Treeen_US
dc.subjectNaive Bayesen_US
dc.subjectHepatitis B Virus Infectionen_US
dc.subjectData Classificationen_US
dc.titleA Comparison of Data Classification Efficiency for Hepatitisen_US
dc.title.alternativeการเปรียบเทียบประสิทธิภาพการจาแนกข้อมูลการเกิดโรคไวรัสตับอักเสบen_US
dc.typeArticleen_US
Appears in Collections:Proceedings of the 15th NPRU National Academic Conference

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