000			03565nam a22004815i 4500
999			_c330848 _d330848
001			330848
003			ES-MaUEC
005			20240111050209.0
006			a||||fo|||| 00| 0
007			cr nn nnnaamaa
008			210303s2021 gw | s |||| 0|eng d
020			_a9783030693596
024	7		_a10.1007/978-3-030-69359-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _erda _dES-MaUEC
050		4	_b2021 EB _aQA76
100	1		_aOwsiński, J. W. _q(Jan W.) _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _948643
245	1	0	_aReverse Clustering _bFormulation, Interpretation and Case Studies _cby Jan W. Owsiński, Jarosław Stańczak, Karol Opara, Sławomir Zadrożny, Janusz Kacprzyk
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Pulishing _c2021
300			_a1 recurso en línea (XVII, 101 páginas) _b27 ilustraciones, 21 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-949X _v957
490	0		_aIntelligent Technologies and Robotics (SpringerNature-42732)
490	0		_aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505	0		_aThe concept of reverse clustering -- Reverse clustering: the essence and the interpretations -- Case studies: an introduction -- The road traffic data -- The chemicals in the natural environment -- Administrative units, Part I -- Administrative units, Part II -- Academic examples -- Summary and conclusions.
520	3		_aThis book presents a new perspective on and a new approach to a wide spectrum of situations, related to data analysis, actually, a kind of a new paradigm. Namely, for a given data set and its partition, whose origins may be of any kind, the authors try to reconstruct this partition on the basis of the data set given, using very broadly conceived clustering procedure. The main advantages of this new paradigm concern the substantive aspects of the particular cases considered, mainly in view of the variety of interpretations, which can be assumed in the framework of the paradigm. Due to the novel problem formulation and the flexibility in the interpretations of this problem and its components, the domains, which are encompassed (or at least affected) by the potential use of the paradigm, include cluster analysis, classification, outlier detection, feature selection, and even factor analysis as well as geometry of the data set. The book is useful for all those who look for new, nonconventional approaches to their data analysis problems.
988			_aSpringer_Robotics_2021
650		7	_2embne _aProceso de datos _9141180
650		7	_2embne _aInteligencia artificial _9413115
700	1		_aStańczak, Jarosław _eautor _4http://id.loc.gov/vocabulary/relators/aut _9677883
700	1		_aOpara, Karol _eautor _4http://id.loc.gov/vocabulary/relators/aut _9677884
700			_aZadrozny, Sławomir. _eautor _4http://id.loc.gov/vocabulary/relators/aut _997912
700	1		_aKacprzyk, Janusz _eautor _4http://id.loc.gov/vocabulary/relators/aut _996945
776	0	8	_iPrinted edition: _z9783030693589
776	0	8	_iPrinted edition: _z9783030693602
776	0	8	_iPrinted edition: _z9783030693619
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-69359-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2021 _da _eIG _zSI