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Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems),Used
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Here's the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. Data Mining: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate databases.Written expressly for database practitioners and professionals, this book begins with a conceptual introduction designed to get you up to speed. This is followed by a comprehensive and stateoftheart coverage of data mining concepts and techniques. Each chapter functions as a standalone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability, keeping your eye on the issues that will affect your project's results and your overall success.Data Mining: Concepts and Techniques is the master reference that practitioners and researchers have long been seeking. It is also the obvious choice for academic and professional classrooms.Classroom Features Available Online: instructor's manual course slides (in PowerPoint) course supplementary readings sample assignments and course projects* Offers a comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data.* Organized as a series of standalone chapters so you can begin anywhere and immediately apply what you learn.* Presents dozens of algorithms and implementation examples, all in easily understood pseudocode and suitable for use in realworld, largescale data mining projects.* Provides indepth, practical coverage of essential data mining topics, including OLAP and data warehousing, data preprocessing, concept description, association rules, classification and prediction, and cluster analysis.* Addresses advanced topics such as mining objectrelational databases, spatial databases, multimedia databases, timeseries databases, text databases, the World Wide Web, and applications in several fields.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: How many pages does this book have? A: This book has five hundred fifty pages. It offers a comprehensive exploration of data mining techniques and principles.
- Q: What is the binding type of this book? A: The book is hardcover. This provides durability and a professional appearance, suitable for both personal and academic use.
- Q: Who is the author of this book? A: The author is Jiawei Han. He is a recognized expert in the field of data mining and data management.
- Q: What topics are covered in this book? A: The book covers essential topics like OLAP, data warehousing, and classification. It also explores advanced themes such as spatial databases and multimedia data.
- Q: Is this book suitable for beginners? A: Yes, the book is suitable for beginners. It begins with a conceptual introduction to help readers understand foundational data mining concepts.
- Q: Can I use this book for classroom instruction? A: Yes, this book is designed for classroom instruction. It includes online resources like instructor manuals and course slides.
- Q: What is the size of the book? A: The book measures seven point five two inches in length, one point two six inches in width, and nine point two five inches in height. Its size makes it easy to handle and read.
- Q: Is there a digital version available? A: No, the product details do not mention a digital version. The book is available in hardcover format only.
- Q: Does this book include practical examples? A: Yes, it includes numerous algorithms and implementation examples. These are presented in easily understood pseudo-code for practical application.
- Q: What features does this book offer for instructors? A: The book offers an instructor's manual, course slides, and supplementary readings. These resources enhance teaching effectiveness.
- Q: Is this book focused on real-world applications? A: Yes, it emphasizes real-world applications of data mining techniques. The authors address utility and feasibility in practical contexts.
- Q: Are there any advanced topics included? A: Yes, the book includes advanced topics like mining object-relational databases and time-series databases. This caters to more experienced readers.
- Q: What kind of algorithms are discussed? A: The book presents dozens of algorithms relevant to data mining. These algorithms are ready for direct use or strategic modification.
- Q: Is this book a good resource for research? A: Yes, this book is an excellent resource for both practitioners and researchers. It serves as a master reference in the field of data mining.
- Q: What is the condition of the used book? A: The book is described as a used book in good condition. This implies it has been well-maintained.
- Q: Does this book address data mining in various fields? A: Yes, it discusses applications of data mining in several fields. This broadens its relevance for diverse professional audiences.