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008			221022s2022 sz | s |||| 0|eng d
020			_a9783030926946
024	7		_a10.1007/978-3-030-92694-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D343 _b2022 EB
100	1		_aLerman, Israël César _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _996533
245	1	0	_aSeriation in Combinatorial and Statistical Data Analysis _cby Israël César Lerman, Henri Leredde
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publising _c2022
300			_a1 recurso en línea (XIV, 277 páginas) _b114 ilustraciones, 6 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aAdvanced Information and Knowledge Processing _x2197-8441
505	0		_aPreface -- Acknowledgements -- General Introduction. Methods and History -- Seriation from Proximity Variance Analysis -- Main Approachs in Seriation. The Attraction Pole Case -- Comparing Geometrical and Ordinal Seriation Methods in Formal and Real Cases -- A New Family of Combinatorial Algorithms in Seriation -- Clustering Methods from Proximity Variance Analysis -- Conclusion and Developments.
520			_aThis monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering. Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically. State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods: Geometric representation methods Algorithmic and Combinatorial methods Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.
988			_aSpringer_Computer_2022
650		7	_2embne _9162648 _aData mining
650		7	_2embne _9138441 _aAnálisis combinatorio
700	1		_aLeredde, Henri _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9685023
776	0	8	_iPrinted edition: _z9783030926939
776	0	8	_iPrinted edition: _z9783030926953
776	0	8	_iPrinted edition: _z9783030926960
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-92694-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b10/2022 _dz _eIG _zSI