| Record ID | marc_columbia/Columbia-extract-20221130-031.mrc:46357823:4248 |
| Source | marc_columbia |
| Download Link | /show-records/marc_columbia/Columbia-extract-20221130-031.mrc:46357823:4248?format=raw |
LEADER: 04248cam a2200829 a 4500
001 15071641
005 20220730230607.0
006 m o d
007 cr cnu---unuuu
008 080507s2007 fluaf ob 001 0 eng d
035 $a(OCoLC)ocn227178704
035 $a(NNC)15071641
040 $aN$T$beng$epn$cN$T$dYDXCP$dOCLCQ$dIDEBK$dOCLCQ$dUIU$dOHS$dMERUC$dOCLCQ$dOCLCF$dOCLCO$dCRCPR$dWAU$dAU@$dOCLCQ$dOCLCO$dOCLCQ$dUAB$dUUM$dOCLCQ$dNLE$dUKMGB$dWYU$dOCLCQ$dLEAUB$dOL$$dOCLCO$dNLW$dOCLCA$dOCLCQ$dOCLCO$dOCLCQ$dSFB$dOCL
015 $aGBB7C6103$2bnb
016 7 $a013689578$2Uk
016 7 $a018425994$2Uk
019 $a191828072$a666919490$a815560564$a1004621324$a1009116442
020 $a9781584888338$q(electronic bk.)
020 $a1584888334$q(electronic bk.)
020 $a9781584888321
020 $a1584888326
020 $a1281274763
020 $a9781281274762
035 $a(OCoLC)227178704$z(OCoLC)191828072$z(OCoLC)666919490$z(OCoLC)815560564$z(OCoLC)1004621324$z(OCoLC)1009116442
037 $aTANDF_184624$bIngram Content Group
050 4 $aQA76.9.D343$bS62 2007eb
060 4 $aQA76.9.D343
072 7 $aCOM$x084010$2bisacsh
072 7 $aCOM$x021000$2bisacsh
072 7 $aCOM$x030000$2bisacsh
072 7 $aK$2bicssc
082 04 $a005.74$222
084 $aST 530$2rvk
049 $aZCUA
100 1 $aSkillicorn, David B.
245 10 $aUnderstanding complex datasets :$bdata mining with matrix decompositions /$cDavid Skillicorn.
260 $aBoca Raton :$bChapman & Hall/CRC Press,$c©2007.
300 $a1 online resource (xxi, 236 pages, 8 unnumbered pages of plates) :$billustrations (some color)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aChapman & Hall/CRC data mining and knowledge discovery series
504 $aIncludes bibliographical references (pages 223-232) and index.
588 0 $aPrint version record.
505 0 $aCover; Title; Copyright; Contents; Preface; List of Figures; Chapter 1: Data Mining; Chapter 2: Matrix decompositions; Chapter 3: Singular Value Decomposition (SVD); Chapter 4: Graph Analysis; Chapter 5: SemiDiscrete Decomposition (SDD); Chapter 6: Using SVD and SDD together; Chapter 7: Independent Component Analysis (ICA); Chapter 8: Non-Negative Matrix Factorization (NNMF); Chapter 9: Tensors; Chapter 10: Conclusion; Appendix A: Matlab Scripts to generate example matrix decompositions; Bibliography; Index.
520 $aDiscusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a range of application areas. This book helps you determine which matrix is appropriate for your dataset and what the results mean. It also shows how matrix decompositions can be used to find documents on the Internet.
650 0 $aData mining.
650 0 $aData structures (Computer science)
650 0 $aComputer algorithms.
650 0 $aAlgorithms.
650 2 $aDatabase Mining
650 2 $aAlgorithms
650 2 $aData Mining
650 6 $aExploration de données (Informatique)
650 6 $aStructures de données (Informatique)
650 6 $aAlgorithmes.
650 7 $aalgorithms.$2aat
650 7 $aCOMPUTERS$xDesktop Applications$xDatabases.$2bisacsh
650 7 $aCOMPUTERS$xDatabase Management$xGeneral.$2bisacsh
650 7 $aCOMPUTERS$xSystem Administration$xStorage & Retrieval.$2bisacsh
650 7 $aAlgorithms.$2fast$0(OCoLC)fst00805020
650 7 $aComputer algorithms.$2fast$0(OCoLC)fst00872010
650 7 $aData mining.$2fast$0(OCoLC)fst00887946
650 7 $aData structures (Computer science)$2fast$0(OCoLC)fst00887978
650 7 $aData Mining$2gnd
650 7 $aMatrizenzerlegung$2gnd
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$aSkillicorn, David B.$tUnderstanding complex datasets.$dBoca Raton : Chapman & Hall/CRC Press, ©2007$z9781584888321$z1584888326$w(DLC) 2007013096$w(OCoLC)105470334
830 0 $aChapman & Hall/CRC data mining and knowledge discovery series.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15071641$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS