000			02025nam a2200253 4500
005			20250716154144.0
008			250716b2020|||||||| |||| 00| 0 eng d
020			_a9781119721826
041			_aEnglish
082			_a001.42
100			_aMakrides, Andreas _eAuthor _96802
100			_aKaragrigoriou, Alex _eCo-Author _96803
100			_aSkiadas, Christos H. _eCo-Author _96794
245			_aData analysis and applications 3: computational, classification, financial, statistical and stochastic methods
250			_a3rd ed.
260			_a New Jersey: _bWiley Data and Cybersecurity, _c2020.
300			_axiii, 236p.
500			_aData analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and statistics packages. This book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis. The chapters included in this volume represent a cross-section of current concerns and research interests in these scientific areas. The material is divided into two parts: Computational Data Analysis, and Classification Data Analysis, with methods for both - providing the reader with both theoretical and applied information on data analysis methods, models and techniques and appropriate applications.
650			_aDistributionally Robust Optimization _96804
650			_aChain Regression Graph Models _96805
650			_a Binary Classification Techniques _96806
856			_uhttps://ieeexplore.ieee.org/servlet/opac?bknumber=9820902
942			_cEB
999			_c1685 _d1685