{"title":"TDApplied：用于机器学习和持久图推断的 R 软件包","authors":"Shael Brown, Reza Farivar-Mohseni","doi":"10.21105/joss.06321","DOIUrl":null,"url":null,"abstract":"Topological data analysis is a collection of tools, based on the mathematical fields of topology and geometry, for finding structure in whole datasets. Its main tool, persistent homology (Edelsbrunner et al., 2000; Zomorodian & Carlsson, 2005), computes a shape descriptor of a dataset called a persistence diagram which encodes information about holes that exist in the dataset (example applications span a variety of areas, see for example Gracia-Tabuenca et al. (2020), Haim Meirom & Bobrowski (2022)","PeriodicalId":503081,"journal":{"name":"Journal of Open Source Software","volume":"33 20","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"TDApplied: An R package for machine learning and\\ninference with persistence diagrams\",\"authors\":\"Shael Brown, Reza Farivar-Mohseni\",\"doi\":\"10.21105/joss.06321\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Topological data analysis is a collection of tools, based on the mathematical fields of topology and geometry, for finding structure in whole datasets. Its main tool, persistent homology (Edelsbrunner et al., 2000; Zomorodian & Carlsson, 2005), computes a shape descriptor of a dataset called a persistence diagram which encodes information about holes that exist in the dataset (example applications span a variety of areas, see for example Gracia-Tabuenca et al. (2020), Haim Meirom & Bobrowski (2022)\",\"PeriodicalId\":503081,\"journal\":{\"name\":\"Journal of Open Source Software\",\"volume\":\"33 20\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Open Source Software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21105/joss.06321\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Open Source Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21105/joss.06321","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TDApplied: An R package for machine learning and
inference with persistence diagrams
Topological data analysis is a collection of tools, based on the mathematical fields of topology and geometry, for finding structure in whole datasets. Its main tool, persistent homology (Edelsbrunner et al., 2000; Zomorodian & Carlsson, 2005), computes a shape descriptor of a dataset called a persistence diagram which encodes information about holes that exist in the dataset (example applications span a variety of areas, see for example Gracia-Tabuenca et al. (2020), Haim Meirom & Bobrowski (2022)
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