3 Review(s)

Data Mining imparts a clear understanding of the algorithms and techniques that can be used to structure large databases and then extract interesting patterns from them. "Written in a reader-friendly manner, the book begins with an introduction to the main analytical techniques used in data mining practices, providing a brief history along with a discussion of related fields such as statistics, pattern recognition, and artificial intelligence. The subsequent chapters are devoted to a thorough coverage of data mining concepts and techniques that include association analysis, classification techniques, clustering, and mining complex data objects. Detailed algorithms are presented with the necessary explanations, pseudo-codes, and analysis to ease their efficient implementation. Extending the discussion further, the book furnishes an overview of data warehousing, with an emphasis on its underlying architecture and query processing, followed by a few case studies to illustrate the practical aspects of the subject. The book concludes with a ten-point vision of the future of data mining. Supplemented with a number of simple illustrative examples and numerous exercises for each technique discussed, the text is ideal for classroom learning." Salient Features Supplies an exhaustive and detailed coverage of algorithms for data mining Lays emphasis on practical applications for all the theory presented Follows a clear and concise style, making it easy to grasp complex concept Provides case studies to bring out the applications of data mining concepts in real-life scenarios