000			04576nam a22004575c 4500
988			_aSpringer_Robotics_2019
999			_c115344 _d115344 _x1
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020			_a9783030156282
024	7		_a10.1007/978-3-030-15628-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2019 EB
245	0	0	_aMachine learning paradigms : _bapplications of learning and analytics in intelligent systems _cedited by George A. Tsihrintzis, Maria Virvou, Evangelos Sakkopoulos, Lakhmi C. Jain
250			_aFirst edition
264		1	_aCham _bSpringer International Publishing _c2019
300			_a1 recurso en línea (XX, 548 páginas) _b139 ilustraciones, 101 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aLearning and Analytics in Intelligent Systems _x2662-3447 _v1
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aChapter 1: Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems -- Chapter 2: A Comparison of Machine Learning Techniques to Predict the Risk of Heart Failure -- Chapter 3: Differential gene Expression Analysis of RNA-seq Data Using Machine Learning for Cancer Research -- Chapter 4: Machine Learning Approaches for Pap-Smear Diagnosis: An Overview -- Chapter 5: Multi-Kernel Analysis Paradigm Implementing the Learning from Loads Approach for Smart Power Systems -- Chapter 6: Conceptualizing and Measuring Energy Security: Geopolitical Dimensions, Data Availability, Quantitative and Qualitative Methods -- Chapter 7: Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learning -- Chapter 8: Airport Data Analysis Using Common Statistical Methods and Knowledge-Based Techniques -- Chapter 9: A Taxonomy and Review of the Network Data Envelopment Analysis Literature -- Chapter 10: Applying Advanced Data Analytics and Machine Learning to Enhance the Safety Control of Dams -- Chapter 11: Analytics and Evolving Landscape of Machine Learning for Emergency Response -- Chapter 12: Social Media Analytics, Types and Methodology -- Chapter 13: Machine Learning Methods for Opinion Mining in Text: The Past and the Future -- Chapter 14: Ship Detection Using Machine Learning and Optical Imagery in the Maritime Environment -- Chapter 15: Video Analytics for Visual Surveillance and Applications: An Overview and Survey -- Chapter 16: Machine Learning in Alternate Testing of Integrated Circuits.
520	3		_aThis book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intelligent systems and related technologies. These disciplines are strongly related and mutually complementary; accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation. To maximize the dissemination of research findings, the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most.
650		7	_2embne _aAprendizaje automático _9166090
650		7	_2embne _aInteligencia artificial _9413115
700	1		_aTsihrintzis, George A _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _9100283
700	1		_aVirvou, Maria _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _9100284
700	1		_aSakkopoulos, Evangelos _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
700			_aJain, Lakhmi C. _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _996931
776	0	8	_iPrinted edition: _z9783030156275
776	0	8	_iPrinted edition: _z9783030156299
776	0	8	_iPrinted edition: _z9783030156305
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-15628-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b12/2019 _eel _zSI