MARC Record from marc_columbia

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001 15408595
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008 171027r20171984enka ob 001 0 eng d
035 $a(OCoLC)on1012884854
035 $a(NNC)15408595
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019 $a1007559215
020 $a9781351460484$q(ePub ebook)
020 $a135146048X$q(ePub ebook)
020 $a9781315139470$q(electronic bk.)
020 $a1315139472$q(electronic bk.)
020 $a9781351460477$q(electronic bk. ;$qMobipocket)
020 $a1351460471$q(electronic bk. ;$qMobipocket)
020 $a9781351460491$q(electronic bk. ;$qPDF)
020 $a1351460498$q(electronic bk. ;$qPDF)
020 $z9780412048418$q(pbk.)
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035 $a(OCoLC)1012884854$z(OCoLC)1007559215
037 $a9781351460484$bIngram Content Group
037 $a9781315139470$bTaylor & Francis
050 4 $aQA278.65$b.B74 1984eb
072 7 $aMAT$x029000$2bisacsh
072 7 $aPBT$2bicssc
082 04 $a519.536$223
084 $a31.73$2bcl
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084 $aDAT 775f$2stub
084 $aDAT 056f$2stub
049 $aZCUA
245 00 $aClassification and regression trees /$cLeo Breiman, University of California, Berkeley; Jerome H. Friedman, Stanford University; Richard A. Olshen, Stanford University; Charles J. Stone, University of California, Berkeley
264 1 $a[Abingdon] :$b[Routledge],$c[2017]
264 4 $c©1984
300 $a1 online resource (x, 358 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
500 $aOriginally published: Boca Raton : Chapman & Hall/CRC, 1984.
520 $aThe methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
504 $aIncludes bibliographical references and indexes
505 0 $aBackground -- Introduction to tree classification -- Right sized trees and honest estimates -- Splitting rules -- Strengthening and interpreting -- Medical diagnosis and prognosis -- Mass spectra classification -- Regression trees -- Bayes rules and partitions -- Optimal pruning -- Construction of trees from a learning sample -- Consistency
588 0 $aPrint version record.
650 0 $aDiscriminant analysis.
650 0 $aRegression analysis.
650 0 $aTrees (Graph theory)
650 2 $aDiscriminant Analysis
650 2 $aRegression Analysis
650 6 $aAnalyse discriminante.
650 6 $aAnalyse de r?egression.
650 6 $aArbres (Th?eorie des graphes)
650 6 $aAnalyse de régression.
650 6 $aArbres (Théorie des graphes)
650 7 $aMATHEMATICS$xProbability & Statistics$xGeneral.$2bisacsh
650 7 $aDiscriminant analysis.$2fast$0(OCoLC)fst00894982
650 7 $aRegression analysis.$2fast$0(OCoLC)fst01432090
650 7 $aTrees (Graph theory)$2fast$0(OCoLC)fst01156136
655 0 $aElectronic books.
700 1 $aBreiman, Leo,$eauthor.
776 08 $iPrint version:$tClassification and regression trees.$d[Abingdon] : [Routledge], [2017?]$z9780412048418$z0412048418$w(OCoLC)38128179
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15408595$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS