02916oam 2200721I 450 991079990790332120200520144314.00-429-10650-51-4398-3928-X10.1201/b11423 (CKB)2670000000175763(EBL)830224(SSID)ssj0001139458(PQKBManifestationID)11651054(PQKBTitleCode)TC0001139458(PQKBWorkID)11213598(PQKB)10959379(SSID)ssj0000580990(PQKBManifestationID)12234789(PQKBTitleCode)TC0000580990(PQKBWorkID)10526328(PQKB)11497283(Au-PeEL)EBL830224(CaPaEBR)ebr10546312(CaONFJC)MIL692885(OCoLC)899154945(OCoLC)785416992(CaSebORM)9781439839287(MiAaPQ)EBC830224(EXLCZ)99267000000017576320180331d2012 uy 0engur|n|---|||||txtccrCost-sensitive machine learning /edited by Balaji Krishnapuram, Shipeng Yu, Bharat Rao1st editionBoca Raton, Fla. :CRC Press,2012.1 online resource (316 p.)Chapman & Hall/CRC machine learning & pattern recognition series"A Chapman & Hall book."1-4665-4817-7 1-322-61603-5 1-4398-3925-5 Includes bibliographical references.pt. 1. Theoretical underpinnings of cost-sensitive machine learning -- pt. 2. Cost-sensitive machine learning applications.In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and cleaningComputational cost for model fitting, validation, and testingCost of collecting features/attributes for test dataCost of user feedback collectionCost of incorrect prediction/classificationCost-Sensitive Machine Learning is one of the first books to provide an overview of the current research efforts and problems in this area. It discusses real-world applications that incorporate the cost oChapman & Hall/CRC machine learning & pattern recognition series.Cost sensitive machine learningMachine learningCost effectivenessMachine learningCost effectiveness.006.31Krishnapuram Balaji1587700Yu Shipeng920799Rao Bharat868293MiAaPQMiAaPQMiAaPQBOOK9910799907903321Cost-sensitive machine learning3875960UNINA