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001			395189
003			ES-MaUEC
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007			cr nn 008mamaa
008			221226s2022 sz | s |||| 0|eng d
020			_a9783031236471
024	7		_a10.1007/978-3-031-23647-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aBusiness Data Analytics _bFirst International Conference, ICBDA 2022, Dehradun, India, October 7-8, 2022, Proceedings _cedited by Rajesh Singh, Valentina Emilia Balas, Arpan Kumar Kar, Anita Gehlot, Shahab Shamshirband.
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XI, 79 páginas) _b54 ilustraciones, 38 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aCommunications in Computer and Information Science _x1865-0937 _v1742
505	0		_aBrain Stroke Prediction using the Artificial Intelligence -- Game Rules Prediction - Winning Strategies using Decision Tree Algorithms -- Quantitative Analysis of the Impact of Demography and Job Profile on the Organizational Commitment of the Faculty Members in the HEI's of Uttarakhand -- Prostate Cancer Data Analytics Using Hybrid ECNN And ERNN Techniques -- A Review on Smart Patient Monitoring and Management in Orthopaedics using Machine Learning -- A Machine Learning Framework for Detection of Fake News.
520			_aThis book constitutes the proceedings of the First International Conference on Business Data Analytics (ICBDA 2022) held in Dehradun, India, in October 7-8, 2022. The purpose of conference is to bring the diverse community of data scientist, machine learning, analytics, and data specialist from all over the world to share their original piece research. The 6 full papers included in this proceedings were selected among 107 submissions in a single-blind review process. The theme of conference includes three sub categories: Predictive Modelling and Data Analytics, Decision Analytics and Support System and Business data Analytics.
776	0	8	_iPrinted edition: _z9783031236464
776	0	8	_iPrinted edition: _z9783031236488
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-23647-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Computer_2022
999			_c395189 _d395189