Please use this identifier to cite or link to this item: https://publication.npru.ac.th/jspui/handle/123456789/1341
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dc.contributor.authorSitichai, Jirayu-
dc.contributor.authorHengpraprohm, Kairung-
dc.contributor.authorHengpraprohm, Supojn-
dc.date.accessioned2021-08-20T08:24:09Z-
dc.date.available2021-08-20T08:24:09Z-
dc.date.issued2021-07-08-
dc.identifier.urihttps://publication.npru.ac.th/jspui/handle/123456789/1341-
dc.description.abstractThe purpose of this research is to compare the efficacy of a model for predicting wine using two data mining techniques, namely the decision tree method and the Bayesian method. The efficiency of the proper classification model for wine prediction was compared using the wine data of the UCI website. Data were analyzed based on the 10-fold cross-validation method using R studio for modeling. The results showed that the decision tree method was most effective. The accuracy was 98.21%, followed by the Bayesian method with an accuracy of 97.54% from the results of this comparison.en_US
dc.publisherThe 13th NPRU National Academic Conference Nakhon Pathom Rajabhat Universityen_US
dc.subjectdata miningen_US
dc.subjectdecision treeen_US
dc.subjectnaïve bayen_US
dc.subjectclassificationen_US
dc.subjectaccuracyen_US
dc.titleA Comparison of Wine Quality Classification Performance by using Data Mining Techniquesen_US
dc.title.alternativeการเปรียบเทียบประสิทธิภาพการจำแนกข้อมูลไวน์ด้วยเทคนิคเหมืองข้อมูลen_US
Appears in Collections:Proceedings of the 13th NPRU National Academic Conference

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