000			02637nam a22003618i 4500
001			CR9780511801389
003			UkCbUP
005			20200124160250.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101021s2000||||enk o ||1 0|eng|d
020			_a9780511801389 (ebook)
020			_z9780521780193 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQ325.5 _b.C75 2000
082	0	0	_a006.3/1 _221
100	1		_aCristianini, Nello, _eauthor.
245	1	3	_aAn introduction to support vector machines : _band other kernel-based learning methods / _cNello Cristianini and John Shawe-Taylor.
246	3		_aAn Introduction to Support Vector Machines & Other Kernel-based Learning Methods
264		1	_aCambridge : _bCambridge University Press, _c2000.
300			_a1 online resource (xiii, 189 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aThe learning methodology -- Linear learning machines -- Kernal-induced feature spaces -- Generalisation theory -- Optimisation theory -- Support vector machines -- Implementation techniques -- Application of support vector machines -- Pseudocode for the SMO algorithm -- Background mathematics.
520			_aThis is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software.
650		0	_aSupport vector machines.
650		0	_aKernel functions.
700	1		_aShawe-Taylor, John, _eauthor.
776	0	8	_iPrint version: _z9780521780193
856	4	0	_uhttps://doi.org/10.1017/CBO9780511801389
999			_c519428 _d519426