000			01802nam a22005055i 4500
001			978-0-387-84858-7
003			DE-He213
005			20130515020622.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387848587 _9978-0-387-84858-7
024	7		_a10.1007/978-0-387-84858-7 _2doi
050		4	_aQA276-280
072		7	_aPBT _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.5 _223
100	1		_aHastie, Trevor.
245	1	4	_aThe Elements of Statistical Learning _h[electronic resource] : _bData Mining, Inference, and Prediction / _cby Trevor Hastie, Robert Tibshirani, Jerome Friedman.
250			_aSecond.
260			_aNew York, NY : _bSpringer New York, _c2009.
300			_bdigital.
490	0		_aSpringer Series in Statistics, _x0172-7397
650		0	_aStatistics.
650		0	_aData mining.
650		0	_aArtificial intelligence.
650		0	_aBioinformatics.
650		0	_aBiology _xData processing.
650		0	_aMathematical statistics.
650	1	4	_aStatistics.
650	2	4	_aStatistical Theory and Methods.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aComputational Biology/Bioinformatics.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aComputer Appl. in Life Sciences.
650	2	4	_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
700	1		_aTibshirani, Robert.
700	1		_aFriedman, Jerome.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387848570
830		0	_aSpringer Series in Statistics, _x0172-7397
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-84858-7
912			_aZDB-2-SMA
999			_c68397 _d68397