| Record ID | marc_columbia/Columbia-extract-20221130-030.mrc:49553522:3876 |
| Source | marc_columbia |
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LEADER: 03876cam a2200685Ia 4500
001 14665302
005 20210607111817.0
006 m o d
007 cr mnu---unuuu
008 090514s2010 flua ob 001 0 eng d
035 $a(OCoLC)ocn456904300
035 $a(NNC)14665302
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020 $a9781439803707$q(electronic bk.)
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020 $a1282296906
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020 $a1466532432
020 $z9781439803691$q(hardback)
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024 7 $a10.1201/9781439803707$2doi
035 $a(OCoLC)456904300$z(OCoLC)816326671$z(OCoLC)899156169$z(OCoLC)991983171$z(OCoLC)994901493$z(OCoLC)1031051565$z(OCoLC)1064052290$z(OCoLC)1086936557
037 $aTANDF_200280$bIngram Content Group
050 4 $aQA76.623$b.I223 2010eb
072 7 $aUXCB$2bicssc
082 04 $a006.3/1$222
049 $aZCUA
100 1 $aIba, Hitoshi.
245 10 $aApplied genetic programming and machine learning /$cHitoshi Iba, Topon Kumar Paul, Yoshihiko Hasegawa.
260 $aBoca Raton :$bCRC Press,$c©2010.
264 4 $c©2010
300 $a1 online resource (xxvi, 327 pages) :$billustrations (some color)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $adata file$2rda
490 1 $aThe CRC Press international series on computational intelligence
504 $aIncludes bibliographical references and (pages 293-319) index.
588 0 $aPrint version record.
505 0 $aCover; Title; Copyright; Contents; List of Tables; List of Figures; Preface; Chapter 1: Introduction; Chapter 2: Genetic Programming; Chapter 3: Numerical Approach to Genetic Programming; Chapter 4: Classification by Ensemble of Genetic Programming Rules; Chapter 5: Probabilistic Program Evolution; Appendix A: GUI Systems and Source Codes; References; Index.
520 $aWhat do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this field, Applied Genetic Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly developing concepts and emerging paradigms, this book outlines how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the searc.
650 0 $aGenetic programming (Computer science)
650 0 $aMachine learning.
650 6 $aProgrammation génétique (Informatique)
650 6 $aApprentissage automatique.
650 7 $aGenetic programming (Computer science)$2fast$0(OCoLC)fst00940075
650 7 $aMachine learning.$2fast$0(OCoLC)fst01004795
655 4 $aElectronic books.
700 1 $aPaul, Topon Kumar.
700 1 $aHasegawa, Yoshihiko.
776 08 $iPrint version:$aIba, Hitoshi.$tApplied genetic programming and machine learning.$dBoca Raton, FL : CRC Press, ©2010$z9781439803691$w(DLC) 2009019804$w(OCoLC)262430622
830 0 $aCRC Press international series on computational intelligence.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio14665302$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS