000			03615nam a22004095i 4500
001			298853
003			MX-SnUAN
005			20170705134244.0
007			cr nn 008mamaa
008			150903s2009 gw | o |||| 0|eng d
020			_a9783540856382 _99783540856382
024	7		_a10.1007/9783540856382 _2doi
035			_avtls000352091
039		9	_a201509030933 _bVLOAD _c201405060300 _dVLOAD _y201402171152 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTA329-348
100	1		_aDelimata, Pawel. _eautor _9335463
245	1	0	_aInhibitory Rules in Data Analysis : _bA Rough Set Approach / _cby Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2009.
300			_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 ; _v163
500			_aSpringer eBooks
505	0		_aMaximal Consistent Extensions of Information Systems -- Minimal Inhibitory Association Rules for Almost All k-Valued Information Systems -- Partial Covers and Inhibitory Decision Rules -- Partial Covers and Inhibitory Decision Rules with Weights -- Classifiers Based on Deterministic and Inhibitory Decision Rules -- Lazy Classification Algorithms Based on Deterministic and Inhibitory Association Rules -- Lazy Classification Algorithms Based on Deterministic and Inhibitory Decision Rules -- Final Remarks.
520			_aThis monograph is devoted to theoretical and experimental study of inhibitory decision and association rules. Inhibitory rules contain on the right-hand side a relation of the kind "attribut does not equal value". The use of inhibitory rules instead of deterministic (standard) ones allows us to describe more completely information encoded in decision or information systems and to design classifiers of high quality. The most important feature of this monograph is that it includes an advanced mathematical analysis of problems on inhibitory rules. We consider algorithms for construction of inhibitory rules, bounds on minimal complexity of inhibitory rules, and algorithms for construction of the set of all minimal inhibitory rules.We also discuss results of experiments with standard and lazy classifiers based on inhibitory rules. These results show that inhibitory decision and association rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction. Inhibitory rules can be also used under the analysis and design of concurrent systems. The results obtained in the monograph can be useful for researchers in such areas as machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory, and logical analysis of data (LAD). The monograph can be used under the creation of courses for graduate students and for Ph.D. studies.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aMoshkov, Mikhail Ju. _eautor _9335464
700	1		_aSkowron, Andrzej. _eautor _9325942
700	1		_aSuraj, Zbigniew. _eautor _9335465
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540856375
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-85638-2 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c298853 _d298853