{"title":"改进的基于遗传算法的XGBoost模型","authors":"ChenJinxiang, Zhaofeng, SunYanguang, YinYilan","doi":"10.1504/ijcat.2020.106571","DOIUrl":null,"url":null,"abstract":"An optimised XGBoost model based on genetic algorithm to search for optimal parameter combinations is proposed in this paper. It was proved that the improved algorithm has better classification eff...","PeriodicalId":46624,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","volume":"10 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Improved XGBoost model based on genetic algorithm\",\"authors\":\"ChenJinxiang, Zhaofeng, SunYanguang, YinYilan\",\"doi\":\"10.1504/ijcat.2020.106571\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An optimised XGBoost model based on genetic algorithm to search for optimal parameter combinations is proposed in this paper. It was proved that the improved algorithm has better classification eff...\",\"PeriodicalId\":46624,\"journal\":{\"name\":\"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijcat.2020.106571\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijcat.2020.106571","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
An optimised XGBoost model based on genetic algorithm to search for optimal parameter combinations is proposed in this paper. It was proved that the improved algorithm has better classification eff...
期刊介绍：
IJCAT addresses issues of computer applications, information and communication systems, software engineering and management, CAD/CAM/CAE, numerical analysis and simulations, finite element methods and analyses, robotics, computer applications in multimedia and new technologies, computer aided learning and training. Topics covered include: -Computer applications in engineering and technology- Computer control system design- CAD/CAM, CAE, CIM and robotics- Computer applications in knowledge-based and expert systems- Computer applications in information technology and communication- Computer-integrated material processing (CIMP)- Computer-aided learning (CAL)- Computer modelling and simulation- Synthetic approach for engineering- Man-machine interface- Software engineering and management- Management techniques and methods- Human computer interaction- Real-time systems
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