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dc.contributor.authorZhao, Zheng Alan
dc.contributor.authorLiu, Huan
dc.date.accessioned2021-02-10T12:58:18Z
dc.date.issued2012-01-01
dc.date.submitted2019-04-11 23:55
dc.date.submitted2020-03-17 03:00:34
dc.date.submitted2020-04-01T10:32:49Z
dc.identifier1004820
dc.identifierOCN: 773311146
dc.identifierhttp://library.oapen.org/handle/20.500.12657/25274
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/36827
dc.description.abstractThis timely introduction to spectral feature selection illustrates the potential of this powerful dimensionality reduction technique in high-dimensional data processing. It presents the theoretical foundations of spectral feature selection, its connections to other algorithms, and its use in handling both large-scale data sets and small sample problems. Readers learn how to use spectral feature selection to solve challenging problems in real-life applications and discover how general feature selection and extraction are connected to spectral feature selection. Source code for the algorithms is available online.
dc.languageEnglish
dc.rightsopen access
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UN Databases::UNF Data mining
dc.subject.otherComputer Science
dc.titleSpectral Feature Selection for Data Mining
dc.typebook
oapen.identifier.doi10.1201/b11426
oapen.relation.isPublishedByfa69b019-f4ee-4979-8d42-c6b6c476b5f0
oapen.relation.isFundedBy969f21b5-ac00-4517-9de2-44973eec6874
oapen.relation.isFundedByb818ba9d-2dd9-4fd7-a364-7f305aef7ee9
oapen.collectionKnowledge Unlatched (KU)
oapen.grant.number102700
oapen.grant.programKU Select 2018: STEM Backlist Books
dc.number102700
dc.relationisFundedByb818ba9d-2dd9-4fd7-a364-7f305aef7ee9


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