Supervised Descriptive Pattern Mining

ISBN-13: 9783030074562 / Angielski / Miękka / 2019 / 185 str.

Sebastian Ventura; Jose Maria Luna

Spis treści

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