DATA MINING CONCEPTS AND TECHNIQUES EBOOK
Data Mining: Concepts and Techniques, 3rd Edition. Jiawei Han, Micheline Kamber, Jian Pei. Database Modeling and Design: Logical Design, 5th Edition. Read "Data Mining: Concepts and Techniques" by Jiawei Han available from Rakuten Kobo. Sign up today and get $5 off your first purchase. Data Mining. Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various.
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This content was uploaded by our users and we assume good faith they have the permission to share this book. If you own the copyright to this book and it is. Editorial Reviews. olhon.info Review. The increasing volume of data in modern business olhon.info: Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) eBook: Jiawei Han, Jian Pei. Data Mining: Concepts and Techniques,. The Morgan Kaufmann Series in Data Management Systems, Jim Gray, Series Editor Morgan Kaufmann Publishers.
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Data mining : concepts and techniques
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Home eBooks Nonfiction Data Mining: Concepts and Techniques Back to Nonfiction. Choose Store. Or, get it for Kobo Super Points! Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data.
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Would you like us to take another look at this review? No, cancel Yes, report it Thanks! You've successfully reported this review. We appreciate your feedback. OK, close. Two additional items are worthy of note: Also, researchers and analysts from other disciplines--for example, epidemiologists, financial analysts, and psychometric researchers--may find the material very useful.
Students should have some background in statistics, database systems, and machine learning and some experience programming. Among the topics are getting to know the data, data warehousing and online analytical processing, data cube technology, cluster analysis, detecting outliers, and trends and research frontiers.
Chapter-end exercises are included. The book is organised in 13 substantial chapters, each of which is essentially standalone, but with useful references to the book's coverage of underlying concepts.
A broad range of topics are covered, from an initial overview of the field of data mining and its fundamental concepts, to data preparation, data warehousing, OLAP, pattern discovery and data classification. The final chapter describes the current state of data mining research and active research areas.
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Please verify that you are not a robot. Would you also like to submit a review for this item? You already recently rated this item. Your rating has been recorded. Write a review Rate this item: Preview this item Preview this item. Data mining: Elsevier Science, Morgan Kaufmann series in data management systems. The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge.
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Since the previous edition's publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understandin. Read more Show all links. Allow this favorite library to be seen by others Keep this favorite library private. Find a copy in the library Finding libraries that hold this item Electronic books Additional Physical Format: Print version: Han, Jiawei.
Data Mining: Concepts and Techniques. Document, Internet resource Document Type: Equips you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets.
This title focuses on important topics in the field:Ron S. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. Some chapters cover basic methods, and others focus on advanced techniques. Advanced Predictive Analytics. Lei Chen. Business Intelligence. Tal Malkin. Please enter recipient e-mail address es. Summing Up: Principles and Practice of Constraint Programming.
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