{"title":"混沌萤火虫算法在回归模型中的变量选择及其在化学计量学中的应用","authors":"Ahmed Alkhateeb, Z. Algamal","doi":"10.1285/I20705948V14N1P266","DOIUrl":null,"url":null,"abstract":"Variable selection is a very helpful procedure for improving computational speed and prediction accuracy by identifying the most important variables that related to the response variable. Regression modeling has received much attention in several science fields. Firefly algorithm is one of the recently efficient proposed nature-inspired algorithms that can efficiently be employed for variable selection. In this work, chaotic firefly algorithm is proposed to perform variable selection for gamma regression model. A real data application related to the chemometrics is conducted to evaluate the performance of the proposed method in terms of prediction accuracy and variable selection criteria. Further, its performance is compared with other methods. The results proved the efficiency of our proposed methods and it outperforms other popular methods.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"14 1","pages":"266-276"},"PeriodicalIF":0.6000,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Variable selection in gamma regression model using chaotic firefly algorithm with application in chemometrics\",\"authors\":\"Ahmed Alkhateeb, Z. Algamal\",\"doi\":\"10.1285/I20705948V14N1P266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Variable selection is a very helpful procedure for improving computational speed and prediction accuracy by identifying the most important variables that related to the response variable. Regression modeling has received much attention in several science fields. Firefly algorithm is one of the recently efficient proposed nature-inspired algorithms that can efficiently be employed for variable selection. In this work, chaotic firefly algorithm is proposed to perform variable selection for gamma regression model. A real data application related to the chemometrics is conducted to evaluate the performance of the proposed method in terms of prediction accuracy and variable selection criteria. Further, its performance is compared with other methods. The results proved the efficiency of our proposed methods and it outperforms other popular methods.\",\"PeriodicalId\":44770,\"journal\":{\"name\":\"Electronic Journal of Applied Statistical Analysis\",\"volume\":\"14 1\",\"pages\":\"266-276\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2021-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Journal of Applied Statistical Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1285/I20705948V14N1P266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Journal of Applied Statistical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1285/I20705948V14N1P266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Variable selection in gamma regression model using chaotic firefly algorithm with application in chemometrics
Variable selection is a very helpful procedure for improving computational speed and prediction accuracy by identifying the most important variables that related to the response variable. Regression modeling has received much attention in several science fields. Firefly algorithm is one of the recently efficient proposed nature-inspired algorithms that can efficiently be employed for variable selection. In this work, chaotic firefly algorithm is proposed to perform variable selection for gamma regression model. A real data application related to the chemometrics is conducted to evaluate the performance of the proposed method in terms of prediction accuracy and variable selection criteria. Further, its performance is compared with other methods. The results proved the efficiency of our proposed methods and it outperforms other popular methods.