Data Mining: Concepts, Models, Methods, and Algorithms - Hardcover

Kantardzic, Mehmed

Hardcover

ISBN 10: 1119516048 ISBN 13: 9781119516040

Publisher: Wiley-IEEE Press, 2019

Synopsis

Presents 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.

About this title

About the Author

MEHMED KANTARDZIC, PHD, is a Professor in the Department of Computer Engineering and Computer Science (CECS) at the University of Louisville, and is Director of the Data Mining Lab and CECS Graduate Programs. He is a member of IEEE, ISCA, KAS, WSEAS, IEE, and SPIE.

From the Back Cover

PRESENTS 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.

From the Inside Flap

PRESENTS 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.

Edition details

• Publisher: Wiley-IEEE Press
• Publication date: 2019
• Language: English
• ISBN 10: 1119516048
• ISBN 13: 9781119516040
• Binding: Hardcover
• Edition number: 3
• Number of pages: 672