{"title":"广义的信息","authors":"Jonathan Bartlett","doi":"10.33014/issn.2640-5652.1.2.bartlett.1","DOIUrl":null,"url":null,"abstract":"Generalized Information (GI) is a measurement of the degree to which a program can be said to generalize a dataset. It is calculated by creating a program to model the data set, measuring the Active Information in the model, and subtracting out the size of the model. Active Information allows GI to be usable with both exact and inexact models.","PeriodicalId":114457,"journal":{"name":"Communications of the Blyth Institute","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Generalized Information\",\"authors\":\"Jonathan Bartlett\",\"doi\":\"10.33014/issn.2640-5652.1.2.bartlett.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Generalized Information (GI) is a measurement of the degree to which a program can be said to generalize a dataset. It is calculated by creating a program to model the data set, measuring the Active Information in the model, and subtracting out the size of the model. Active Information allows GI to be usable with both exact and inexact models.\",\"PeriodicalId\":114457,\"journal\":{\"name\":\"Communications of the Blyth Institute\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications of the Blyth Institute\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33014/issn.2640-5652.1.2.bartlett.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":"Communications of the Blyth Institute","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33014/issn.2640-5652.1.2.bartlett.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generalized Information (GI) is a measurement of the degree to which a program can be said to generalize a dataset. It is calculated by creating a program to model the data set, measuring the Active Information in the model, and subtracting out the size of the model. Active Information allows GI to be usable with both exact and inexact models.
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