000			03032nam a22005055i 4500
001			978-1-84628-219-5
003			DE-He213
005			20201213200617.0
007			cr nn 008mamaa
008			100301s2005 xxk| s |||| 0|eng d
020			_a9781846282195 _9978-1-84628-219-5
024	7		_a10.1007/1-84628-219-5 _2doi
050		4	_aQ337.5
050		4	_aTK7882.P3
072		7	_aUYQP _2bicssc
072		7	_aCOM016000 _2bisacsh
082	0	4	_a006.4 _223
100	1		_aAbe, Shigeo. _eauthor.
245	1	0	_aSupport Vector Machines for Pattern Classification _h[electronic resource] / _cby Shigeo Abe.
264		1	_aLondon : _bSpringer London, _c2005.
300			_aXIV, 343p. 110 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aAdvances in Pattern Recognition
505	0		_aTwo-Class Support Vector Machines -- Multiclass Support Vector Machines -- Variants of Support Vector Machines -- Training Methods -- Feature Selection and Extraction -- Clustering -- Kernel-Based Methods -- Maximum-Margin Multilayer Neural Networks -- Maximum-Margin Fuzzy Classifiers -- Function Approximation.
520			_aI was shocked to see a student’s report on performance comparisons between support vector machines (SVMs) and fuzzy classi?ers that we had developed withourbestendeavors.Classi?cationperformanceofourfuzzyclassi?erswas comparable, but in most cases inferior, to that of support vector machines. This tendency was especially evident when the numbers of class data were small. I shifted my research e?orts from developing fuzzy classi?ers with high generalization ability to developing support vector machine–based classi?ers. This book focuses on the application of support vector machines to p- tern classi?cation. Speci?cally, we discuss the properties of support vector machines that are useful for pattern classi?cation applications, several m- ticlass models, and variants of support vector machines. To clarify their - plicability to real-world problems, we compare performance of most models discussed in the book using real-world benchmark data. Readers interested in the theoretical aspect of support vector machines should refer to books such as [109, 215, 256, 257].
650		0	_aComputer science.
650		0	_aArtificial intelligence.
650		0	_aText processing (Computer science.
650		0	_aOptical pattern recognition.
650	1	4	_aComputer Science.
650	2	4	_aPattern Recognition.
650	2	4	_aDocument Preparation and Text Processing.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aControl Engineering.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781852339296
830		0	_aAdvances in Pattern Recognition
856	4	0	_uhttp://dx.doi.org/10.1007/1-84628-219-5
912			_aZDB-2-SCS
950			_aComputer Science (Springer-11645)
999			_c13064 _d13064