000			02194nam a22003618i 4500
001			CR9780511809682
003			UkCbUP
005			20201015164226.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101021s2004||||enk o ||1 0|eng|d
020			_a9780511809682 (ebook)
020			_z9780521813976 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQ325.5 _b.S475 2004
082	0	0	_a006.3/1 _222
100	1		_aShawe-Taylor, John, _eauthor.
245	1	0	_aKernel methods for pattern analysis / _cJohn Shawe-Taylor, Nello Cristianini.
264		1	_aCambridge : _bCambridge University Press, _c2004.
300			_a1 online resource (xiv, 462 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).
520			_aKernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed from lectures and tutorials, fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to use for standard pattern discovery problems in fields such as bioinformatics, text analysis, image analysis. Secondly it provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.
650		0	_aMachine learning.
650		0	_aAlgorithms.
650		0	_aKernel functions.
650		0	_aPattern perception _xData processing.
700	1		_aCristianini, Nello, _eauthor.
776	0	8	_iPrint version: _z9780521813976
856	4	0	_uhttps://doi.org/10.1017/CBO9780511809682
999			_c121126 _d121126