{"title":"在线建模算法的可执行分类法","authors":"S. Bunton","doi":"10.1109/DCC.1997.581959","DOIUrl":null,"url":null,"abstract":"This paper gives an overview of our decomposition of a group of existing and novel on-line modeling algorithms into component parts, which can be implemented as a cross product of predominantly independent sets. The result is all of the following: a test bed for executing controlled experiments with algorithm components, a frame work that unifies existing techniques and defines novel techniques, and a taxonomy for describing on-line modeling algorithms precisely and completely in a way that enables meaningful comparison.","PeriodicalId":403990,"journal":{"name":"Proceedings DCC '97. Data Compression Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An executable taxonomy of on-line modeling algorithms\",\"authors\":\"S. Bunton\",\"doi\":\"10.1109/DCC.1997.581959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper gives an overview of our decomposition of a group of existing and novel on-line modeling algorithms into component parts, which can be implemented as a cross product of predominantly independent sets. The result is all of the following: a test bed for executing controlled experiments with algorithm components, a frame work that unifies existing techniques and defines novel techniques, and a taxonomy for describing on-line modeling algorithms precisely and completely in a way that enables meaningful comparison.\",\"PeriodicalId\":403990,\"journal\":{\"name\":\"Proceedings DCC '97. Data Compression Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC '97. Data Compression Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.1997.581959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings DCC '97. Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1997.581959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An executable taxonomy of on-line modeling algorithms
This paper gives an overview of our decomposition of a group of existing and novel on-line modeling algorithms into component parts, which can be implemented as a cross product of predominantly independent sets. The result is all of the following: a test bed for executing controlled experiments with algorithm components, a frame work that unifies existing techniques and defines novel techniques, and a taxonomy for describing on-line modeling algorithms precisely and completely in a way that enables meaningful comparison.