000			02158nam a22002057a 4500
003			AIT
005			20230828173559.0
008			230828b ii ||||| |||| 00| 0 eng d
020			_a978-1-119-51604-0
040			_cAIT
082			_a005.74 _bKAN
100			_aKantardzic, Mehmed _913537
245			_aData Mining: Concepts, Models, Methods, and Algorithms
250			_a3rd ed
260			_aNew Jersey, _bJohn Wiley & Sons, Inc ; _c2020.
300			_axix, 639 p.
520			_aPresents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author―a noted expert on the topic―explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.
650			_aData Mining I MCA _913538
942			_2ddc _cMCA_BK _n0
999			_c7085 _d7085