| Record ID | marc_columbia/Columbia-extract-20221130-015.mrc:33325470:2914 |
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LEADER: 02914cam a2200373Ia 4500
001 7094705
005 20221130205839.0
008 090130t20092009nyua b 001 0 eng
020 $a9780387848570
020 $a0387848576
029 1 $aOHX$bhar080114565
035 $a(OCoLC)ocn300478243
035 $a(NNC)7094705
035 $a7094705
040 $aNUI$cNUI$dYDXCP$dCTB$dCDX$dBWX$dIXA$dOHX$dOrLoB-B
050 4 $aQ325.75$b.H37 2009
082 04 $a006.3'1 22$222
100 1 $aHastie, Trevor.$0http://id.loc.gov/authorities/names/n90646512
245 14 $aThe elements of statistical learning :$bdata mining, inference, and prediction /$cTrevor Hastie, Robert Tibshirani, Jerome Friedman.
250 $a2nd ed.
260 $aNew York :$bSpringer,$c[2009], ©2009.
300 $axxii, 745 pages :$billustrations ;$c24 cm.
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
490 1 $aSpringer series in statistics
504 $aIncludes bibliographical references and indexes.
505 00 $g1.$tIntroduction --$g2.$tOverview of Supervised Learning --$g3.$tLinear Methods for Regression --$g4.$tLinear Methods for Classification --$g5.$tBasis Expansions and Regularization --$g6.$tKernel Smoothing Methods --$g7.$tModel Assessment and Selection --$g8.$tModel Inference and Averaging --$g9.$tAdditive Models, Trees, and Related Methods --$g10.$tBoosting and Additive Trees --$g11.$tNeural Networks --$g12.$tSupport Vector Machines and Flexible Discriminants --$g13.$tPrototype Methods and Nearest-Neighbors --$g14.$tUnsupervised Learning --$g15.$tRandom Forests --$g16.$tEnsemble Learning --$g17.$tUndirected Graphical Models --$g18.$tHigh-Dimensional Problems: p >> N.
520 1 $a"During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics."--BOOK JACKET.
650 0 $aSupervised learning (Machine learning)$0http://id.loc.gov/authorities/subjects/sh94008290
700 1 $aTibshirani, Robert.$0http://id.loc.gov/authorities/names/n88665311
700 1 $aFriedman, J. H.$q(Jerome H.)$0http://id.loc.gov/authorities/names/n89648779
830 0 $aSpringer series in statistics.$0http://id.loc.gov/authorities/names/n42023188
852 00 $bmat$hQ325.75$i.H37 2009g
852 00 $bmat$hQ325.75$i.H37 2009g