| 000 | 04824cam a2200949Ia 4500 | ||
|---|---|---|---|
| 001 | ocn729724626 | ||
| 003 | OCoLC | ||
| 005 | 20171119084417.0 | ||
| 006 | m o d | ||
| 007 | cr cn||||||||| | ||
| 008 | 110609s2011 njua ob 001 0 eng d | ||
| 020 |
_a9781118023471 _q(electronic bk.) |
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| 020 |
_a1118023471 _q(electronic bk.) |
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| 020 | _a9781283098687 | ||
| 020 | _z9780470641835 | ||
| 020 |
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| 020 | _z1118023463 | ||
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_a(OCoLC)729724626 _z(OCoLC)726329153 _z(OCoLC)732956377 _z(OCoLC)741451118 _z(OCoLC)754717771 _z(OCoLC)778448327 _z(OCoLC)816840042 |
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| 037 |
_a10.1002/9781118023471 _bWiley InterScience _nhttp://www3.interscience.wiley.com |
||
| 040 |
_aDG1 _beng _epn _cDG1 _dIDEBK _dYDXCP _dE7B _dCDX _dOCLCQ _dCOD _dN$T _dOCLCQ _dDEBSZ _dOCLCQ _dOCLCA _dUKDOC _dOCLCQ _dRIV _dNLGGC _dOCLCQ _dOCLCF _dDEBBG _dOCLCQ _dCOO _dOCLCQ |
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| 049 | _aMAIN | ||
| 050 | 4 |
_aQ325.5 _b.K85 2011 |
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| 060 | 4 | _aQ 325.5 | |
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_aCOM _x005030 _2bisacsh |
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_aCOM _x004000 _2bisacsh |
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| 082 | 0 | 4 |
_a006.3/1 _222 |
| 100 | 1 | _aKulkarni, Sanjeev. | |
| 245 | 1 | 3 |
_aAn elementary introduction to statistical learning theory / _cSanjeev Kulkarni, Gilbert Harman. _h[electronic resource] |
| 260 |
_aHoboken, N.J. : _bWiley, _c©2011. |
||
| 300 |
_a1 online resource (1 volume) : _billustrations. |
||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 | _aWiley series in probability and statistics | |
| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | _aIntroduction: Classification, Learning, Features, and Applications -- Probability -- Probability Densities -- The Pattern Recognition Problem -- The Optimal Bayes Decision Rule -- Learning from Examples -- The Nearest Neighbor Rule -- Kernel Rules -- Neural Networks: Perceptrons -- Multilayer Networks -- PAC Learning -- VC Dimension -- Infinite VC Dimension -- The Function Estimation Problem -- Learning Function Estimation -- Simplicity -- Support Vector Machines -- Boosting. | |
| 520 | _a"A joint endeavor from leading researchers in the fields of philosophy and electrical engineering An Introduction to Statistical Learning Theory provides a broad and accessible introduction to rapidly evolving field of statistical pattern recognition and statistical learning theory. Exploring topics that are not often covered in introductory level books on statistical learning theory, including PAC learning, VC dimension, and simplicity, the authors present upper-undergraduate and graduate levels with the basic theory behind contemporary machine learning and uniquely suggest it serves as an excellent framework for philosophical thinking about inductive inference"--Back cover. | ||
| 588 | 0 | _aPrint version record. | |
| 650 | 0 |
_aMachine learning _xStatistical methods. |
|
| 650 | 0 | _aPattern recognition systems. | |
| 650 | 2 | _aArtificial Intelligence. | |
| 650 | 2 | _aPattern Recognition, Automated. | |
| 650 | 2 | _aStatistics as Topic. | |
| 650 | 0 | 4 |
_aAprenentatge automàtic _xMètodes estadístics. |
| 650 | 4 | _aReconeixement de formes (Informàtica) | |
| 650 | 7 |
_aCOMPUTERS _xEnterprise Applications _xBusiness Intelligence Tools. _2bisacsh |
|
| 650 | 7 |
_aCOMPUTERS _xIntelligence (AI) & Semantics. _2bisacsh |
|
| 650 | 7 |
_aMachine learning _xStatistical methods. _2fast _0(OCoLC)fst01004801 |
|
| 650 | 7 |
_aPattern recognition systems. _2fast _0(OCoLC)fst01055266 |
|
| 650 | 0 | 7 |
_aMaschinelles Lernen. _0(DE-588c)4193754-5 _2swd |
| 650 | 0 | 7 |
_aStatistik. _0(DE-588c)4056995-0 _2swd |
| 655 | 4 | _aLlibres electrònics. | |
| 655 | 4 | _aElectronic books. | |
| 700 | 1 | _aHarman, Gilbert. | |
| 710 | 2 | _aWiley InterScience (Online service) | |
| 776 | 0 | 8 |
_iPrint version: _aKulkarni, Sanjeev. _tElementary introduction to statistical learning theory. _dHoboken, N.J. : Wiley, ©2011 _z9781118023471 _w(OCoLC)726329153 |
| 830 | 0 | _aWiley series in probability and statistics. | |
| 856 | 4 | 0 |
_uhttp://onlinelibrary.wiley.com/book/10.1002/9781118023471 _zWiley Online Library |
| 942 |
_2ddc _cBK |
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| 999 |
_c205074 _d205074 |
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