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008			160324s2016 xxk| s |||| 0|eng d
020			_a9781447167938
040			_aES-MaUEC _bspa
050		4	_aQA164 _b.L47 2016 EB
082	0	4	_a006.312
100	1		_aLerman, Israël César _0Local _0http://id.loc.gov/authorities/names/nb2017013235 _996533
245	1	0	_aFoundations and Methods in Combinatorial and Statistical Data Analysis and Clustering _cby Israël César Lerman
250			_a1st ed.
264		1	_aLondon _bSpringer London _c2016
300			_a1 recurso en línea (XXIV, 647 páginas) _b54 ilustraciones
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aAdvanced Information and Knowledge Processing _x1610-3947
505	0		_aPreface -- On Some Facets of the Partition Set of a Finite Set -- Two Methods of Non-hierarchical Clustering -- Structure and Mathematical Representation of Data -- Ordinal and Metrical Analysis of the Resemblance Notion -- Comparing Attributes by a Probabilistic and Statistical Association I -- Comparing Attributes by a Probabilistic and Statistical Association II -- Comparing Objects or Categories Described by Attributes -- The Notion of zNaturaly Class, Tools for its Interpretation. The Classifiability Concept -- Quality Measures in Clustering -- Building a Classification Tree -- Applying the LLA Method to Real Data -- Conclusion and Thoughts for Future Works.
520			_aThis book offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ideas within this very active field. With extensive introductions, formal and mathematical developments and real case studies, this book provides readers with a deeper understanding of the mutual relationships between these methods, which are clearly expressed with respect to three facets: logical, combinatorial and statistical. Using relational mathematical representation, all types of data structures can be handled in precise and unified ways which the author highlights in three stages: Clustering a set of descriptive attributes Clustering a set of objects or a set of object categories Establishing correspondence between these two dual clusterings Tools for interpreting the reasons of a given cluster or clustering are also included. < Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering will be a valuable resource for students and researchers who are interested in the areas of Data Analysis, Clustering, Data Mining and Knowledge Discovery.
650		7	_aData mining _2embne _9162648
710	2		_aSpringerLink (Online service) _0Local _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729 _9106996
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-1-4471-6793-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9781447167938
907			_a.b12936753 _b10-10-17 _c21-11-16
942			_2lcc _cLE
945			_aEBOOK EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11612496 _z30-06-17
988	0	0	_aEBOOK, EBSPRINGER, GOBI_sep2018
988			_aEbook_one2one
998			_aSI _a_alco _a_vill _b10/2018 _cm _dz _ek _feng _gxxk _h0
999			_c84397 _d84397 _x1