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Chapter 2: Getting to Know Your Data
Data Objects and Attribute Types
Basic Statistical Descriptions of Data
Data Visualization
Measuring Data Similarity and Dissimilarity
Summary
Chapter 3: Data Preprocessing
Data Preprocessing: An Overview
Data Quality
Major Tasks in Data Preprocessing
Data Cleaning
Data Integration
Data Reduction
Data Transformation and Data Discretization
Summary
Chapter 4: Data Warehousing and On-line Analytical Processing
Data Warehouse: Basic Concepts
Data Warehouse Modeling: Data Cube and OLAP
Data Warehouse Design and Usage
Data Warehouse Implementation
Data Generalization by Attribute-Oriented Induction
Summary
Chapter 5: Data Cube Technology
Efficient Methods for Data Cube Computation
Data Cubes for Advanced Applications
Knowledge Discovery with Data Cubes
Summary
Chapter 6: Mining Frequent Patterns, Association and Correlations: Basic Concepts and
Methods
Chapter 7 : Advanced Frequent Pattern Mining
Frequent Pattern and Association Mining: A Road Map
Pattern Mining in Multi-Level, Multi-Dimensional Space
Exploring Alternative Approaches to Improve Efficiency and Scalability
Mining Beyond Typical Frequent Patterns
Constraint-Based Frequent Pattern Mining
Advanced Applications of Frequent Patterns
Summary
Chapter 8. Classification: Basic Concepts
Classification: Basic Concepts
Decision Tree Induction
Bayes Classification Methods
Rule-Based Classification
Model Evaluation and Selection
Techniques to Improve Classification Accuracy: Ensemble Methods
Handling Different Kinds of Cases in Classification
Summary
Chapter 9. Classification: Advanced Methods
Bayesian Belief Networks
Classification by Neural Networks
Support Vector Machines
Pattern-Based Classification
Lazy Learners (or Learning from Your Neighbors)
Other Classification Methods
Summary
Chapter 10. Cluster Analysis: Basic Concepts and Methods
Chapter 11. Cluster Analysis: Advanced Methods
Chapter 12. Outlier Analysis
Why outlier analysis? Identifying and handling of outliers
Distribution-Based Outlier Detection: A Statistics-Based Approach
Classification-Based Outlier Detection
Clustering-Based Outlier Detection
Distance-Based Outlier Detection
Local Outlier Analysis: A Density-Based Approach
Deviation-Based Outlier Detection
Isolation-Based Method: From Isolation Tree to Isolation Forest
Outlier Detection in High Dimensional Data
Intrusion Detection
Summary
Chapter 13. Trends and Research Frontiers in Data Mining
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