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| 001 | 13465 | ||
| 009 | 060757299 | ||
| 003 | http://www.sudoc.fr/060757299 | ||
| 005 | 20250630092329.0 | ||
| 010 |
_a0387987800 _brel. |
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| 010 | _a978-0-387-98780-4 | ||
| 073 | 0 | _a9780587987304 | |
| 090 | _a13465 | ||
| 099 |
_tOUVR _zALEX26152 |
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| 100 | _a20020503d2000 k y0frey50 ba | ||
| 101 | 0 |
_aeng _eeng _feng _2639-2 |
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| 102 | _aUS | ||
| 105 | _aa a 001yy | ||
| 106 | _ar | ||
| 181 |
_6z01 _ctxt _2rdacontent |
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| 181 | 1 |
_6z01 _ai# _bxxxe## |
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| 182 |
_6z01 _cn _2rdamedia |
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| 182 | 1 |
_6z01 _an |
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| 183 | 1 |
_6z01 _anga _2RDAfrCarrier |
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| 200 | 1 |
_aThe nature of statistical learning theory _fVladimir N. Vapnik |
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| 205 | _a2nd edition | ||
| 214 | 0 |
_aNew York _cSpringer |
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| 214 | 4 | _dC 2000 | |
| 215 |
_a1 volume (xix-314 pages) _cillustrations, couverture illustrée en couleur _d24 cm |
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| 225 | 2 | _aStatistics for engineering and information science | |
| 320 | _aBibliographie p. [301]-309. Index | ||
| 330 | _aThe aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques | ||
| 410 |
_0068927835 _tStatistics for engineering and information science |
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| 606 |
_3027940373 _aApprentissage automatique _3027545555 _xMéthodes statistiques _2rameau |
||
| 606 |
_3032889690 _aModèles stochastiques d'apprentissage _2rameau |
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| 676 | _a006.310 151 | ||
| 676 | _a519.5 | ||
| 686 |
_a68T05 _c2010 _2msc |
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| 686 |
_a60F10 _c2010 _2msc |
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| 686 |
_a62G99 _c2010 _2msc |
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| 700 | 1 |
_3034266208 _aVapnik _bVladimir Naoumovitch _4070 |
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