000			03180nam a22003975i 4500
001			298501
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008			150903s2008 gw | o |||| 0|eng d
020			_a9783540789796 _99783540789796
024	7		_a10.1007/9783540789796 _2doi
035			_avtls000351768
039		9	_a201509030930 _bVLOAD _c201405060255 _dVLOAD _y201402171145 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTA329-348
100	1		_aBull, Larry. _eeditor. _9328934
245	1	0	_aLearning Classifier Systems in Data Mining / _cedited by Larry Bull, Ester Bernadó-Mansilla, John Holmes.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2008.
300			_aIx, 230 páginas 65 ilustraciones _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aStudies in Computational Intelligence, _x1860-949X ; _v125
500			_aSpringer eBooks
505	0		_aLearning Classifier Systems in Data Mining: An Introduction -- Data Mining in Proteomics with Learning Classifier Systems -- Improving Evolutionary Computation Based Data-Mining for the Process Industry: The Importance of Abstraction -- Distributed Learning Classifier Systems -- Knowledge Discovery from Medical Data: An Empirical Study with XCS -- Mining Imbalanced Data with Learning Classifier Systems -- XCS for Fusing Multi-Spectral Data in Automatic Target Recognition -- Foreign Exchange Trading Using a Learning Classifier System -- Towards Clustering with Learning Classifier Systems -- A Comparative Study of Several Genetic-Based Supervised Learning Systems.
520			_aJust over thirty years after Holland first presented the outline for Learning Classifier System paradigm, the ability of LCS to solve complex real-world problems is becoming clear. In particular, their capability for rule induction in data mining has sparked renewed interest in LCS. This book brings together work by a number of individuals who are demonstrating their good performance in a variety of domains. The first contribution is arranged as follows: Firstly, the main forms of LCS are described in some detail. A number of historical uses of LCS in data mining are then reviewed before an overview of the rest of the volume is presented. The rest of this book describes recent research on the use of LCS in the main areas of machine learning data mining: classification, clustering, time-series and numerical prediction, feature selection, ensembles, and knowledge discovery.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aBernadó-Mansilla, Ester. _eeditor. _9334924
700	1		_aHolmes, John. _eeditor. _9334925
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540789789
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-78979-6 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c298501 _d298501