Data Mining Techniques
Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems\ Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support\ The authors build on their reputation for concise, clear, and practical explanations of...
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The unparalleled author team of Berry and Linoff are back with an invaluable revised edition to their groundbreaking textThe world of data mining has changed tremendously since the publication of the first edition of Data Mining Techniques in 1997. For the most part, the underlying algorithms have remained the same, but the software in which the algorithms are imbedded, the databases to which they are applied, and the business problems they are used to solve have all grown and evolved. With that in mind, Michael Berry and Gordon Linoff–the leading authorities on the use of data mining techniques for business applications–have written a new edition to show you how to harness fundamental data mining methods and techniques to solve common types of business problems. Berry and Linoff’s years of hands-on data mining experience is reflected in every chapter of this extensively updated and revised edition. They discuss core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis. In addition, they provide an overview of data mining best practices. Each chapter covers a new data mining technique and then immediately explains how to apply the technique for improved marketing, sales, and customer support. The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining for both business professionals and students.With more than forty percent new and updated material, this second edition of Data Mining Techniques shows you how to: Create stable and accurate predictive modelsPrepare data for analysis Create the necessary infrastructure for data mining at your companyThe companion Web site provides exercises for each chapter, plus data that can be used to test out the various data mining techniques in the book.
AcknowledgmentsAbout the authorsIntroductionCh. 1Why and what is data mining?1Ch. 2The virtuous cycle of data mining21Ch. 3Data mining methodology and best practices43Ch. 4Data mining applications in marketing and customer relationship management87Ch. 5The lure of statistics : data mining using familiar tools123Ch. 6Decision trees165Ch. 7Artificial neural networks211Ch. 8Nearest neighbor approaches : memory-based reasoning and collaborative filtering257Ch. 9Market basket analysis and association rules287Ch. 10Link analysis321Ch. 11Automatic cluster detection349Ch. 12Knowing when to worry : hazard functions and survival analysis in marketing383Ch. 13Genetic algorithms421Ch. 14Data mining throughout the customer life cycle447Ch. 15Data warehousing, OLAP, and data mining473Ch. 16Building the data mining environment513Ch. 17Preparing data for mining539Ch. 18Putting data mining to work597Index615
