05507nam 2200697 a 450 991046136390332120200520144314.01-283-17117-197866131711770-12-381480-4(CKB)2670000000092948(EBL)729031(OCoLC)741491891(SSID)ssj0000507801(PQKBManifestationID)12207267(PQKBTitleCode)TC0000507801(PQKBWorkID)10550628(PQKB)10134696(MiAaPQ)EBC729031(CaSebORM)9780123814791(PPN)170267180(Au-PeEL)EBL729031(CaPaEBR)ebr10483440(CaONFJC)MIL317117(EXLCZ)99267000000009294820110405d2012 uy 0engur|n|---|||||rdacontentrdamediardacarrierData mining[electronic resource] concepts and techniques /Jiawei Han, Micheline Kamber, Jian Pei3rd ed.Burlington, Mass. Elsevierc20121 recurso en línea (745 páginas)The Morgan Kaufmann series in data management systemsDescription based upon print version of record.0-12-381479-0 Includes bibliographical references and index.Front Cover; Data Mining: Concepts and Techniques; Copyright; Dedication; Table of Contents; Foreword; Foreword to Second Edition; Preface; Acknowledgments; About the Authors; Chapter 1. Introduction; 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?; 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; Chapter 2. Getting to Know Your Data; 2.1 Data Objects and Attribute Types2.2 Basic Statistical Descriptions of Data2.3 Data Visualization; 2.4 Measuring Data Similarity and Dissimilarity; 2.5 Summary; 2.6 Exercises; 2.7 Bibliographic Notes; Chapter 3. Data Preprocessing; 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; Chapter 4. Data Warehousing and Online Analytical Processing; 4.1 Data Warehouse: Basic Concepts; 4.2 Data Warehouse Modeling: Data Cube and OLAP; 4.3 Data Warehouse Design and Usage4.4 Data Warehouse Implementation4.5 Data Generalization by Attribute-Oriented Induction; 4.6 Summary; 4.7 Exercises; 4.8 Bibliographic Notes; Chapter 5. Data Cube Technology; 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; Chapter 6. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods; 6.1 Basic Concepts; 6.2 Frequent Itemset Mining Methods6.3 Which Patterns Are Interesting?-Pattern Evaluation Methods6.4 Summary; 6.5 Exercises; 6.6 Bibliographic Notes; Chapter 7. Advanced Pattern Mining; 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; Chapter 8. Classification: Basic Concepts; 8.1 Basic Concepts; 8.2 Decision Tree Induction8.3 Bayes Classification Methods8.4 Rule-Based Classification; 8.5 Model Evaluation and Selection; 8.6 Techniques to Improve Classification Accuracy; 8.7 Summary; 8.8 Exercises; 8.9 Bibliographic Notes; Chapter 9. Classification: Advanced Methods; 9.1 Bayesian Belief Networks; 9.2 Classification by Backpropagation; 9.3 Support Vector Machines; 9.4 Classification Using Frequent Patterns; 9.5 Lazy Learners (or Learning from Your Neighbors); 9.6 Other Classification Methods; 9.7 Additional Topics Regarding Classification; 9.8 Summary; 9.9 Exercises; 9.10 Bibliographic NotesChapter 10. Cluster Analysis: Basic Concepts and MethodsThe 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. 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 withMorgan Kaufmann series in data management systems.Data miningElectronic books.Data mining.006.3/12Han Jiawei145005Kamber Micheline145006Pei Jian868267MiAaPQMiAaPQMiAaPQBOOK9910461363903321Data mining2466281UNINA