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007			cr nn 008mamaa
008			150903s2010 xxk| o |||| 0|eng d
020			_a9781848822603 _99781848822603
024	7		_a10.1007/9781848822603 _2doi
035			_avtls000344400
039		9	_a201509030403 _bVLOAD _c201405050306 _dVLOAD _y201402061256 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ334-342
100	1		_aBerthold, Michael R. _eautor _9322267
245	1	0	_aGuide to Intelligent Data Analysis : _bHow to Intelligently Make Sense of Real Data / _cby Michael R. Berthold, Christian Borgelt, Frank Höppner, Frank Klawonn.
264		1	_aLondon : _bSpringer London : _bImprint: Springer, _c2010.
300			_axiii, 394 páginas 141 ilustraciones, 78 ilustraciones en color. _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		_aTexts in Computer Science, _x1868-0941 ; _v42
500			_aSpringer eBooks
505	0		_aPractical Data Analysis: An Example -- Project Understanding -- Data Understanding -- Principles of Modeling -- Data Preparation -- Finding Patterns -- Finding Explanations -- Finding Predictors -- Evaluation and Deployment.
520			_aEach passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle - solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of "drowning in information, but starving for knowledge" the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: Guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring Equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion Provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms Includes numerous examples using R and KNIME, together with appendices introducing the open source software Integrates illustrations and case-study-style examples to support pedagogical exposition Supplies further tools and information at the associated website: http://www.idaguide.net/ This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one's exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aBorgelt, Christian. _eautor _9314992
700	1		_aHöppner, Frank. _eautor _9322268
700	1		_aKlawonn, Frank. _eautor _9314993
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781848822597
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-84882-260-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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