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Description
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Data Mining Techniques is the leading introductory book on data mining, with more than 24,000 copies sold. Written by internationally recognized authorities on the business uses of data mining, this book not only explains the core data mining concepts and techniques, but more importantly shows how to apply the concepts to solve practical business problems. The authors are masters at clearly and concisely explaining complex ideas to a general audience, which makes this book popular among both business managers and college students. Given the success of this book in the college market, the authors will be develop a Website that provides student exercises for each chapter, plus data that students and others can use to test out the various data mining techniques in the book.
This second edition of Data Mining Techniques (more than 40% new and updated) 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. These include:
o Improving response rates to direct marketing campaigns
o Identifying new customer segments
o Estimating credit risk
Each chapter covers a new data mining technique, and then immediately show 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.
The authors cover core datat mining techinques, including:
o Decision trees,
o Neural networks
o Collaborative filtering
o Association rules, link analysis, clustering
o Survival analysis
The authors also provide an overview of data mining best practices and how to perform data mining using simple tools like Excel. More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining at your company.
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