{"title":"肥胖症数据集的机器学习分类器比较评价","authors":"A. Ramya, K. Rohini","doi":"10.1109/ICCS54944.2021.00016","DOIUrl":null,"url":null,"abstract":"Datamining is very important in modern world. Collection of many types of data we find (knowledge discovery process) the essential information from hidden things. So, data mining is very important to extract the essential hidden data. Data mining with machine learning algorithmsis effective to mine the essential data and it is very fast-growing technology. Few ML algorithms are compared using BMI based. Obesity is BMI level is equal to 30 or above 30, so this disease is very complex. Obesity will affect the quality of life like depression, lower work achievement, disability. In this paper we applied classification machine learning algorithms like KNN, XGB, Logistic Regression, DT and compared those algorithms in obesity data.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Comparative evaluation of machine learning classifiers with Obesity dataset\",\"authors\":\"A. Ramya, K. Rohini\",\"doi\":\"10.1109/ICCS54944.2021.00016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Datamining is very important in modern world. Collection of many types of data we find (knowledge discovery process) the essential information from hidden things. So, data mining is very important to extract the essential hidden data. Data mining with machine learning algorithmsis effective to mine the essential data and it is very fast-growing technology. Few ML algorithms are compared using BMI based. Obesity is BMI level is equal to 30 or above 30, so this disease is very complex. Obesity will affect the quality of life like depression, lower work achievement, disability. In this paper we applied classification machine learning algorithms like KNN, XGB, Logistic Regression, DT and compared those algorithms in obesity data.\",\"PeriodicalId\":340594,\"journal\":{\"name\":\"2021 International Conference on Computing Sciences (ICCS)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computing Sciences (ICCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCS54944.2021.00016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computing Sciences (ICCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCS54944.2021.00016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative evaluation of machine learning classifiers with Obesity dataset
Datamining is very important in modern world. Collection of many types of data we find (knowledge discovery process) the essential information from hidden things. So, data mining is very important to extract the essential hidden data. Data mining with machine learning algorithmsis effective to mine the essential data and it is very fast-growing technology. Few ML algorithms are compared using BMI based. Obesity is BMI level is equal to 30 or above 30, so this disease is very complex. Obesity will affect the quality of life like depression, lower work achievement, disability. In this paper we applied classification machine learning algorithms like KNN, XGB, Logistic Regression, DT and compared those algorithms in obesity data.