{"title":"Wine Quality Prediction Using Data Mining","authors":"P. Shruthi","doi":"10.1109/ICATIECE45860.2019.9063846","DOIUrl":null,"url":null,"abstract":"Certifying the quality of food product is the major concern of the country. The citizens of the country are recommended to use only quality assured products. The same thing need to be applied for the wine industry also. The quality of wine need to be assessed and it should be classified into different category based on the quality assessment. Data mining is the right approach to achieve this as it extracts the useful information by analyzing the data set. In this paper, the samples of different wines with their attributes required for quality assurance is collected and different data mining classification algorithms- Naive Bayes, Simple Logistic, KStar, JRip, J48 are applied on it. The wine will be classified into three main categories and the accuracy of the algorithms are compared.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICATIECE45860.2019.9063846","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Certifying the quality of food product is the major concern of the country. The citizens of the country are recommended to use only quality assured products. The same thing need to be applied for the wine industry also. The quality of wine need to be assessed and it should be classified into different category based on the quality assessment. Data mining is the right approach to achieve this as it extracts the useful information by analyzing the data set. In this paper, the samples of different wines with their attributes required for quality assurance is collected and different data mining classification algorithms- Naive Bayes, Simple Logistic, KStar, JRip, J48 are applied on it. The wine will be classified into three main categories and the accuracy of the algorithms are compared.