03211nam 22007933 450 991031645110332120241107095306.097866139085759781000023077100002307997804291071910429107196978128359612112835961219781439862100143986210910.1201/b11426 (CKB)2550000000079286(EBL)830232(OCoLC)773311146(SSID)ssj0000580573(PQKBManifestationID)11374600(PQKBTitleCode)TC0000580573(PQKBWorkID)10607449(PQKB)10279946(MiAaPQ)EBC830232(ScCtBLL)4895e3cf-d91f-4079-b2ca-734762788389(CaSebORM)9781439862100(MiAaPQ)EBC7245454(Au-PeEL)EBL7245454(OCoLC)817812230(ODN)ODN0004679216(EXLCZ)99255000000007928620231110d2012 uy 0engur|n|---|||||txtccrSpectral feature selection for data mining /Zheng Alan Zhao, Huan Liu1st ed.2011Boca Raton, FL :CRC Press,[2012]©20121 online resource (216 p.)Chapman & Hall/CRC data mining and knowledge discovery series"A Chapman & Hall book."9781138112629 1138112623 9781439862094 1439862095 Includes bibliographical references and index.Front Cover; Dedication; Contents; Preface; Authors; Symbol Description; 1. Data of High Dimensionality and Challenges; 2. Univariate Formulations for Spectral Feature Selection; 3. Multivariate Formulations; 4. Connections to Existing Algorithms; 5. Large-Scale Spectral Feature Selection; 6. Multi-Source Spectral Feature Selection; ReferencesSpectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervised feature selection. The book explores the latest research achievements, sheds light on new research directions, and stimulates readers to make the next creative breakthroughs. It presents the intrinsic ideas behind spectral feature selection, its thChapman & Hall/CRC data mining and knowledge discovery series.Data miningData mining.006.3/12006.312BUS061000COM000000COM012040bisacshZhao Zheng(Zheng Alan),918257Liu Huan1958-MiAaPQMiAaPQMiAaPQBOOK9910316451103321Spectral feature selection for data mining4156481UNINA