Supervised Descriptive Pattern Mining
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Chapter 1. Introduction to Pattern Mining
1.1 Importance of patterns
1.2 Type of patterns
1.3 Quality measures in pattern mining
1.3.1 Objective interestingness measures
1.3.2 Subjective interestingness measures
1.4 Scalability issues
1.4 Supervised descriptive local patterns
Chapter 2. Subgroup Discovery
2.1 Introduction
2.2 Task definition
2.3 Quality measures
2.4 Models in subgroup discovery
Chapter 3. Contrast sets
3.1 Introduction
3.2 Task definition
3.3 Algorithms
Chapter 4. Emerging patterns
4.1 Introduction
4.2 Task definition
4.3 Algorithms
Chapter 5. Class Association rules
5.1 Introduction
5.2 Task definition
5.2.1 Association rules
5.2.2 Class association rules
5.2.3 Associative classification
5.3 Algorithms
Chapter 6. Exceptional models
6.1 Introduction
6.2 Exceptional model mining
6.3 Exceptional preference mining
6.4 Exceptional pattern mining
6.5 Algorithms
Chapter 7. Applications of supervised descriptive local patterns
7.1 Introduction
7.2 Subgroup discovery
7.3 Contrast sets
7.4 Emerging patterns
7.5 Exceptional models
7.6 Class association rules
Chapter 8. Additional tasks related to supervised pattern mining
8.1 Change mining
8.2 Mining of closed sets for labeled data
8.3 Bump hunting
8.4 Impact rules
8.5 Discrimination discovery
8.6 Context aware
Autor: | Ventura, Sebastian |
Nakladatel: | Springer, Berlin |
Rok vydání: | 2019 |
Jazyk : | Angličtina |
Vazba: | Hardback |
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