| Record ID | harvard_bibliographic_metadata/ab.bib.11.20150123.full.mrc:799372030:1171 |
| Source | harvard_bibliographic_metadata |
| Download Link | /show-records/harvard_bibliographic_metadata/ab.bib.11.20150123.full.mrc:799372030:1171?format=raw |
LEADER: 01171cam a2200349Ia 4500
001 011896134-9
005 20140417085656.0
008 090130s2009 nyua b 001 0 eng
020 $a9780387848570
020 $a0387848576
035 0 $aocn300478243
040 $aNUI$cNUI$dYDXCP$dCTB$dCDX$dBWX$dIXA$dOHX
050 4 $aQ325.75$b.H37 2009
082 04 $a006.3'1 22$222
100 1 $aHastie, Trevor.
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,$cc2009.
300 $axxii, 745 p. :$bill. ;$c24 cm.
440 0 $aSpringer series in statistics$x0172-7397
504 $aIncludes bibliographical references (p. [699]-727) and indexes.
650 0 $aSupervised learning (Machine learning)
650 0 $aStatistics.
650 0 $aData mining.
650 0 $aArtificial intelligence.
650 0 $aBioinformatics.
650 0 $aBiology$xData processing.
650 0 $aMathematical statistics.
700 1 $aTibshirani, Robert.
700 1 $aFriedman, J. H.$q(Jerome H.)
988 $a20090320
906 $0OCLC