• Dedication • Foreword • Foreword to Second Edition • Preface • Organization of the Book • To the Instructor • To the Student • To the Professional • Book Web Sites with Resources • Acknowledgments • Third Edition of the Book • Second Edition of the Book • First Edition of the Book • About the Authors • 1. Introduction • Publisher Summary • 1.1 Why Data Mining? • 1.2 What Is Data Mining? • 1.3 What Kinds of Data Can Be Mined? • 1.4 What Kinds of Patterns Can Be Mined?
Data Mining Han And Kamber Solution Manual Pdf
• 1.5 Which Technologies Are Used? • 1.6 Which Kinds of Applications Are Targeted? • 1.7 Major Issues in Data Mining • 1.8 Summary • 1.9 Exercises • 1.10 Bibliographic Notes • 2.
Data Mining: Concepts and Techniques, 3rd Edition. Jiawei Han, Micheline Kamber, Jian Pei. Database Modeling and Design: Logical Design, 5th Edition. Teorey, Sam S. Lightstone, Thomas P. Foundations of Multidimensional and Metric Data Structures. Joe Celko's SQL for. Data Mining: Concepts and Techniques. Solution Manual. Jiawei Han and Micheline Kamber. The University of Illinois at Urbana-Champaign c Morgan Kaufmann, 2006. Note: For Instructors' reference only. Do not distribute!
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Getting to Know Your Data • Publisher Summary • 2.1 Data Objects and Attribute Types • 2.2 Basic Statistical Descriptions of Data • 2.3 Data Visualization • 2.4 Measuring Data Similarity and Dissimilarity • 2.5 Summary • 2.6 Exercises • 2.7 Bibliographic Notes • 3. Data Preprocessing • Publisher Summary • 3.1 Data Preprocessing: An Overview • 3.2 Data Cleaning • 3.3 Data Integration • 3.4 Data Reduction • 3.5 Data Transformation and Data Discretization • 3.6 Summary • 3.7 Exercises • 3.8 Bibliographic Notes • 4. Data Warehousing and Online Analytical Processing • Publisher Summary • 4.1 Data Warehouse: Basic Concepts • 4.2 Data Warehouse Modeling: Data Cube and OLAP • 4.3 Data Warehouse Design and Usage • 4.4 Data Warehouse Implementation • 4.5 Data Generalization by Attribute-Oriented Induction • 4.6 Summary • 4.7 Exercises • Bibliographic Notes • 5. Data Cube Technology • Publisher Summary • 5.1 Data Cube Computation: Preliminary Concepts • 5.2 Data Cube Computation Methods • 5.3 Processing Advanced Kinds of Queries by Exploring Cube Technology • 5.4 Multidimensional Data Analysis in Cube Space • 5.5 Summary • 5.6 Exercises • 5.7 Bibliographic Notes • 6. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods • Publisher Summary • 6.1 Basic Concepts • 6.2 Frequent Itemset Mining Methods • 6.3 Which Patterns Are Interesting? Rapidshare unigine engine download free. —Pattern Evaluation Methods • 6.4 Summary • 6.5 Exercises • 6.6 Bibliographic Notes • 7. Advanced Pattern Mining • Publisher Summary • 7.1 Pattern Mining: A Road Map • 7.2 Pattern Mining in Multilevel, Multidimensional Space • 7.3 Constraint-Based Frequent Pattern Mining • 7.4 Mining High-Dimensional Data and Colossal Patterns • 7.5 Mining Compressed or Approximate Patterns • 7.6 Pattern Exploration and Application • 7.7 Summary • 7.8 Exercises • 7.9 Bibliographic Notes • 8.