DATA MINING TECHNIQUES BY BERRY AND LINOFF PDF

Michael J. Berry , Gordon S. 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 complex concepts, making this book the perfect introduction to data mining More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis. The Virtuous Cycle of Data Mining. Data Mining Methodology and Best Practices. Hypothesis Testing.

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Michael J. Berry , Gordon S. 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 complex concepts, making this book the perfect introduction to data mining More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis.

The Virtuous Cycle of Data Mining. Data Mining Methodology and Best Practices. Hypothesis Testing. Translate the Business Problem. Create a Model Set. Data Mining Applications in Marketing. Market Basket Analysis and Association Rules. Automatic Cluster Detection. Similarity and Distance. Hazard Functions. Genetic Algorithms. Data Mining throughout the Customer Life Cycle. Data Mining Using Familiar Tools. The C5 Pruning Algorithm.

Artificial Neural Networks. Building the Data Mining Environment. Preparing Data for Mining. Putting Data Mining to Work. Data Mining Techniques 2Nd Ed. They each have more than a decade of experience applying data mining techniques to business problems in marketing and customer relationship management. Why and What Is Data Mining? Build Models. Link Analysis. Decision Trees.

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Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, 3rd Edition

Du kanske gillar. Ladda ned. Spara som favorit. Laddas ned direkt. The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk.

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Anyone interested in automating and improving decisions should have this book. It is one of the classic works on data mining and well worth the read. I really liked the book both because it is well Michael J. Berry , Gordon S. Who will remain a loyal customer and who won't? What kind of marketing approach is most likely to increase sales?

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