{"title":"基于迭代决策树算法的学术浮力分类研究","authors":"Qiaoling Ye, Ting Zhou, Zheng Huang","doi":"10.1109/ECICE55674.2022.10042816","DOIUrl":null,"url":null,"abstract":"The relationship between family risk factors and academic buoyancy has received attention through empirical studies, such as Bad family atmosphere, frequent family conflicts, disharmonious parent-child relationship, etc. Other family factors have an impact on the development of academic buoyancy, but there is less research on its combination characteristics. Based on the actual education scene of a middle school, we first score students’ academic buoyancy as the dependent variable and then collect nine types of variables representing family risk factors as independent variables. Then, a classification model between independent and dependent variables is constructed by using the decision tree method. The model provides a guideline for teaching work, and the test result of the model is ideal.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Academic Buoyancy Classification Based on Iterative Decision Tree Algorithm\",\"authors\":\"Qiaoling Ye, Ting Zhou, Zheng Huang\",\"doi\":\"10.1109/ECICE55674.2022.10042816\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The relationship between family risk factors and academic buoyancy has received attention through empirical studies, such as Bad family atmosphere, frequent family conflicts, disharmonious parent-child relationship, etc. Other family factors have an impact on the development of academic buoyancy, but there is less research on its combination characteristics. Based on the actual education scene of a middle school, we first score students’ academic buoyancy as the dependent variable and then collect nine types of variables representing family risk factors as independent variables. Then, a classification model between independent and dependent variables is constructed by using the decision tree method. The model provides a guideline for teaching work, and the test result of the model is ideal.\",\"PeriodicalId\":282635,\"journal\":{\"name\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECICE55674.2022.10042816\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECICE55674.2022.10042816","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Academic Buoyancy Classification Based on Iterative Decision Tree Algorithm
The relationship between family risk factors and academic buoyancy has received attention through empirical studies, such as Bad family atmosphere, frequent family conflicts, disharmonious parent-child relationship, etc. Other family factors have an impact on the development of academic buoyancy, but there is less research on its combination characteristics. Based on the actual education scene of a middle school, we first score students’ academic buoyancy as the dependent variable and then collect nine types of variables representing family risk factors as independent variables. Then, a classification model between independent and dependent variables is constructed by using the decision tree method. The model provides a guideline for teaching work, and the test result of the model is ideal.