TY  - BOOK
AU  - Han,Jiawei
AU  - Kamber,Micheline
TI  - Data mining: concepts and techniques 
SN  - 9780123814791
AV  - QA76.9.D343 H233 2012
PY  - 2012///
CY  - Burlington, MA
PB  - Elsevier
KW  - Data mining
N1  - includes index; Chapter 1. Introduction --; Index; 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 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--; 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 iscretization--; 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 Usage--; 4.4 Data Warehouse Implementation--; 4.5 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 Methods--; 6. 3 Which Patterns Are Interesting?--Pattern Evaluation Methods--; 6.4 Summary--; 6.5 Exercises--; 6.6 Bibliographic Notes--; Chapter t 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 Induction--; 8.3 Bayes Classification Methods--; 8.4 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 Notes--; Chapter 10. Cluster Analysis: Basic Concepts and Methods--; 10.1 Cluster Analysis--; 10.2 Partitioning Methods--; 10.t3 Hierarchical Methods--; 10.4 Density-Based Methods--; 10.5 Grid-Based Methods--; 10.6 Evaluation of Clustering--; 10.7 Summary--; 10.8 Exercises--; 10.9 Bibliographic Notes--; Chapter 11. Advanced Cluster Analysis--; 11.1 Probabilistic Model-Based Clustering--; 11.2 Clustering High-Dimensional Data--; 11.--; 3 Clustering Graph and Network Data--; 11.4 Clustering with Constraints--; 11.5 Summary--; 11.6 Exercises--; 11.7 Bibliographic Notes--; Chapter 12. Outlier Detection--; 12.1 Outliers and Outlier Analysis--; 12.2 Outlier Detection Methods--; 12. 3 Statistical Approaches--; 12.4 Proximity-Based Approaches--; 12.5 Clustering-Based Approaches--; 12.6 Classification-Based Approaches--; 12.7 Mining Contextual and Collective Outliers--; 12.8 Outlier Detection in High-Dimensional Data--; 12.9 Summary--; 12.10 Exercises12.11 Bibliographic Notes--; Chapter 13. Data Mining Trends and Research Frontiers--; 13.1 Mining Complex Data Types--; 13.2 Other Methodologies of Data Mining--; 1--; 3.3 Data Mining Applications--; 13.4 Data Mining and Society--; 13.5 Data Mining Trends--; 13.6 Summary--; 13.7 Exercises--; 13.8 Bibliographic Notes--; Bibliography--; Index
ER  -