{"title":"机器学习的可靠性","authors":"Thomas Grote, Konstantin Genin, Emily Sullivan","doi":"10.1111/phc3.12974","DOIUrl":null,"url":null,"abstract":"Issues of reliability are claiming center‐stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts in statistics and machine learning – as far as they are concerned with reliability.","PeriodicalId":40011,"journal":{"name":"Philosophy Compass","volume":"77 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reliability in Machine Learning\",\"authors\":\"Thomas Grote, Konstantin Genin, Emily Sullivan\",\"doi\":\"10.1111/phc3.12974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Issues of reliability are claiming center‐stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts in statistics and machine learning – as far as they are concerned with reliability.\",\"PeriodicalId\":40011,\"journal\":{\"name\":\"Philosophy Compass\",\"volume\":\"77 1\",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-04-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Philosophy Compass\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/phc3.12974\",\"RegionNum\":1,\"RegionCategory\":\"哲学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"PHILOSOPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Philosophy Compass","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/phc3.12974","RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"PHILOSOPHY","Score":null,"Total":0}
Issues of reliability are claiming center‐stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts in statistics and machine learning – as far as they are concerned with reliability.
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