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007 cr nn 008maaau
008 100623s2009 nyu j eng d
020 _a9780387848587 (electronic bk.)
035 _a(Springer)978-0-387-84857-0
040 _aUKM
050 4 _aQ325.75
_b.H37 2009
082 0 4 _a006.31
_222
090 _aQ325.75
_b.H356 2009
100 1 _aHastie, Trevor-
_eauthor.
245 1 4 _aThe elements of statistical learning
_h[electronic resource] :
_bdata mining, inference, and prediction /
_cby Jerome Friedman, Robert Tibshirani, Trevor Hastie.
250 _a2nd ed.
260 _aNew York, NY :
_bSpringer-Verlag New York,
_c2009.
300 _axxii, 745 p. :
_bill., digital ;
_c24 cm.
440 0 _aSpringer series in statistics,
_x0172-7397
650 0 _aSupervised learning (Machine learning)
650 2 4 _aStatistical Theory and Methods.
650 1 _aStatistics.
650 2 _aStatistics for Engineering, Physics, Computer Science, Chemistry & Geosciences.
650 2 _aComputer Appl. in Life Sciences.
650 2 _aArtificial Intelligence (incl. Robotics)
650 2 _aComputational Biology/Bioinformatics.
650 2 _aData Mining and Knowledge Discovery.
700 1 _aTibshirani, Robert.
700 1 _aFriedman, J. H.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
856 4 0 _uhttps://eresourcesptsl.ukm.remotexs.co/user/login?url=http://dx.doi.org/10.1007/b94608
907 _a.b14746712
_b2024-02-02
_c2019-11-12
942 _n0
_kQ325.75 .H356 2009
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998 _ae0001
_b2010-10-06
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