{"title":"基于特征提取的集成学习方法的微阵列癌症分类","authors":"Anita Bai, Swati Hira","doi":"10.1504/ijdats.2021.118014","DOIUrl":null,"url":null,"abstract":"Microarray cancer datasets generally contain many features with a small number of samples, so initially we need to reduce redundant features to allow faster convergence. To address this issue, we p...","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"112 1","pages":"244-263"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Microarray cancer classification using feature extraction-based ensemble learning method\",\"authors\":\"Anita Bai, Swati Hira\",\"doi\":\"10.1504/ijdats.2021.118014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Microarray cancer datasets generally contain many features with a small number of samples, so initially we need to reduce redundant features to allow faster convergence. To address this issue, we p...\",\"PeriodicalId\":38582,\"journal\":{\"name\":\"International Journal of Data Analysis Techniques and Strategies\",\"volume\":\"112 1\",\"pages\":\"244-263\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Data Analysis Techniques and Strategies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijdats.2021.118014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Analysis Techniques and Strategies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijdats.2021.118014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
Microarray cancer classification using feature extraction-based ensemble learning method
Microarray cancer datasets generally contain many features with a small number of samples, so initially we need to reduce redundant features to allow faster convergence. To address this issue, we p...