000			03405nam a22004455i 4500
999			_c368405 _d368405 _x1
001			368405
003			ES-MaUEC
005			20230102121732.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			220319s2022 si | s |||| 0|eng d
020			_a9789811689307
024	7		_a10.1007/978-981-16-8930-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2022 EB
245	0	0	_aAdvances in Machine Learning for Big Data Analysis _cedited by Satchidananda Dehuri, Yen-Wei Chen
250			_aFirst edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIX, 239 páginas) _b97 ilustraciones, 72 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aIntelligent Systems Reference Library _x1868-4408 _v218
505	0		_aDeep Learning for Supervised Learning -- Deep Learning for Unsupervised Learning -- Support Vector Machine for Regression -- Support Vector Machine for Classification -- Decision Tree for Regression -- Higher Order Neural Networks -- Competitive Learning -- Semi-supervised Learning -- Multi-objective Optimization Techniques -- Techniques for Feature Selection/Extraction -- Techniques for Task Relevant Big Data Analysis -- Techniques for Post Processing Task in Big Data Analysis -- Customer Relationship Management.
520			_aThis book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems.
988			_aSpringer_Robotics_2022
650		7	_2embne _9166090 _aAprendizaje automático
650		7	_2embne _9495511 _aDatos masivos
700	1		_aDehuri, Satchidananda _eeditor literario _4 _4http://id.loc.gov/vocabulary/relators/edt _998235
700	1		_aChen, Yen-Wei _eeditor literario _4 _4http://id.loc.gov/vocabulary/relators/edt _997417
776	0	8	_iPrinted edition: _z9789811689291
776	0	8	_iPrinted edition: _z9789811689314
776	0	8	_iPrinted edition: _z9789811689321
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-8930-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2022 _dz _eIG _zSI