{"title":"在检验数据独立性假设时,将经典的Edgeworth-Edleton-Pearson检验与双分形检验相结合,减少了神经网络的样本量要求","authors":"V. Volchikhin, A. Ivanov, Y. Serikova","doi":"10.21685/2072-3059-2023-1-1","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":33992,"journal":{"name":"Izvestiia vysshikh uchebnykh zavedenii Povolzhskii regionTekhnicheskie nauki","volume":"20 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reducing sample size requirements for neural network combining the classical Edgeworth-Edleton-Pearson test and its two-fractal counterparts when testing the data independence hypothesis\",\"authors\":\"V. Volchikhin, A. Ivanov, Y. Serikova\",\"doi\":\"10.21685/2072-3059-2023-1-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":33992,\"journal\":{\"name\":\"Izvestiia vysshikh uchebnykh zavedenii Povolzhskii regionTekhnicheskie nauki\",\"volume\":\"20 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Izvestiia vysshikh uchebnykh zavedenii Povolzhskii regionTekhnicheskie nauki\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21685/2072-3059-2023-1-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Izvestiia vysshikh uchebnykh zavedenii Povolzhskii regionTekhnicheskie nauki","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21685/2072-3059-2023-1-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reducing sample size requirements for neural network combining the classical Edgeworth-Edleton-Pearson test and its two-fractal counterparts when testing the data independence hypothesis