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Spectral feature selection for data mining

Spectral feature selection for data mining (3회 대출)

자료유형
단행본
개인저자
Zhao, Zheng (Zheng Alan) Liu, Huan, 1958-.
서명 / 저자사항
Spectral feature selection for data mining / Zheng Alan Zhao, Huan Liu.
발행사항
Boca Raton, FL :   CRC Press,   c2012.  
형태사항
xv, 195 p., [8] p. of plates : ill. (some col.) ; 25 cm.
총서사항
Chapman & Hall/CRC data mining and knowledge discovery series
ISBN
9781439862094 (hardcover : alk. paper) 1439862095 (hardcover : alk. paper)
서지주기
Includes bibliographical references and index.
일반주제명
Data mining.
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008 130503s2012 fluaf b 001 0 eng
010 ▼a 2011041746
020 ▼a 9781439862094 (hardcover : alk. paper)
020 ▼a 1439862095 (hardcover : alk. paper)
035 ▼a (KERIS)REF000016851122
040 ▼a DLC ▼c DLC ▼d YDX ▼d BTCTA ▼d UKMGB ▼d YDXCP ▼d BWX ▼d CDX ▼d DLC ▼d 211009
050 0 0 ▼a QA76.9.D343 ▼b Z53 2012
082 0 0 ▼a 006.3/12 ▼2 23
084 ▼a 006.312 ▼2 DDCK
090 ▼a 006.312 ▼b Z63s
100 1 ▼a Zhao, Zheng ▼q (Zheng Alan)
245 1 0 ▼a Spectral feature selection for data mining / ▼c Zheng Alan Zhao, Huan Liu.
260 ▼a Boca Raton, FL : ▼b CRC Press, ▼c c2012.
300 ▼a xv, 195 p., [8] p. of plates : ▼b ill. (some col.) ; ▼c 25 cm.
490 1 ▼a Chapman & Hall/CRC data mining and knowledge discovery series
504 ▼a Includes bibliographical references and index.
650 0 ▼a Data mining.
700 1 ▼a Liu, Huan, ▼d 1958-.
830 0 ▼a Chapman & Hall/CRC data mining and knowledge discovery series.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 006.312 Z63s 등록번호 121225055 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

Data of High Dimensionality and ChallengesDimensionality Reduction TechniquesFeature Selection for Data MiningSpectral Feature SelectionOrganization of the Book Univariate Formulations for Spectral Feature SelectionModeling Target Concept via Similarity Matrix The Laplacian Matrix of a GraphEvaluating Features on the Graph An Extension for Feature Ranking Functions Spectral Feature Selection via RankingRobustness Analysis for SPECDiscussions Multivariate Formulations The Similarity Preserving Nature of SPECA Sparse Multi-Output Regression FormulationSolving the L2,1-Regularized Regression ProblemEfficient Multivariate Spectral Feature SelectionA Formulation Based on Matrix Comparison Feature Selection with Proposed Formulations Connections to Existing AlgorithmsConnections to Existing Feature Selection Algorithms Connections to Other Learning ModelsAn Experimental Study of the AlgorithmsDiscussions Large-Scale Spectral Feature SelectionData Partitioning for Parallel Processing MPI for Distributed Parallel ComputingParallel Spectral Feature SelectionComputing the Similarity Matrix in ParallelParallelization of the Univariate Formulations Parallel MRSFParallel MCSF Discussions Multi-Source Spectral Feature SelectionCategorization of Different Types of KnowledgeA Framework Based on Combining Similarity MatricesA Framework Based on Rank AggregationExperimental ResultsDiscussions References Index


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