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Introduction to Data Mining,New
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Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics.Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.QuotesThis book provides a comprehensive coverage of important data mining techniques. Numerous examples are provided to lucidly illustrate the key concepts.Sanjay Ranka, University of FloridaIn my opinion this is currently the best data mining text book on the market. I like the comprehensive coverage which spans all major data mining techniques including classification, clustering, and pattern mining (association rules).Mohammed Zaki, Rensselaer Polytechnic Institute
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- Q: How many pages does this book have? A: This book has seven hundred ninety-two pages. It provides comprehensive details on data mining techniques and concepts.
- Q: What is the binding type of this book? A: This book is hardcover. The durable binding is designed to withstand regular use while maintaining its quality.
- Q: What are the dimensions of this book? A: The book measures seven point seventy-two inches in length, one point sixty-one inches in width, and nine point forty-one inches in height.
- Q: Who are the authors of this book? A: The authors are Tan, Pang-Ning; Steinbach, Michael; and Kumar, Vipin. They are well-respected figures in the field of data mining.
- Q: What is the target audience for this book? A: This book is suitable for beginners learning about data mining. It starts with fundamental concepts and advances to complex algorithms.
- Q: Is prior knowledge of mathematics required to understand this book? A: No, only a modest background in mathematics is required. The book is designed to be accessible to newcomers.
- Q: How should I care for this hardcover book? A: To keep this book in good condition, store it in a dry place and avoid exposing it to direct sunlight for prolonged periods.
- Q: Can I easily find examples in this book? A: Yes, numerous examples are provided throughout the text. These examples help to illustrate key concepts clearly.
- Q: Is this book suitable for advanced learners? A: Yes, advanced learners can benefit from this book. It includes both basic and advanced concepts, covering a wide range of topics.
- Q: What should I do if my book arrives damaged? A: If your book arrives damaged, contact customer support for assistance. They can provide instructions on returning or exchanging the book.
- Q: What techniques does this book cover? A: The book covers major data mining techniques including classification, clustering, and pattern mining, among others.
- Q: Does this book include practical applications? A: Yes, it includes numerous practical examples that demonstrate the application of data mining techniques in real-world scenarios.
- Q: Is this book recommended by experts? A: Yes, it is highly recommended by experts in the field, including quotes from notable academics praising its comprehensive coverage.
- Q: What category does this book fall under? A: This book falls under the Data Mining category. It is specifically tailored for those interested in learning this field.
- Q: What publisher released this book? A: The book is published by Pearson, a well-known publisher in the field of educational materials.