Exploiting the power of group differences: using patterns to solve data analysis problems

Acknowledgments......Page 16
 Importance of Group Differences......Page 18
 Summary of Chapters......Page 19
 Known Uses of Group Differences via Emerging Patterns......Page 22
 Unique Properties of Emerging Pattern Based Methods......Page 23
 Scenarios Where Emerging Patterns Are Especially Useful......Page 24
 Related Topics Not Covered in This Book......Page 25
 Data Instances and Datasets......Page 26
 Attribute Binning and Discretization......Page 27
 Patterns, Matching Datasets, Supports, and Frequent Patterns......Page 28
 Equivalence Classes, Closed Patterns, Minimal Generators, and Borders......Page 29
 Illustrating Examples......Page 30
 Basics of Emerging Patterns......Page 32
 BorderDiff: A Simple, Flexible Emerging Pattern Mining Algorithm......Page 35
 What Emerging Patterns Can Represent......Page 37
 Comparison with Association Rules, Confidence, and Odds Ratio......Page 38
 Pointers to Sections Illustrating Uses of Emerging Patterns......Page 40
 Traditional Analysis of Group Differences......Page 41
 Discussion of Related Issues......Page 42
 Background Materials on Classification......Page 44
 The CAEP Approach......Page 45
  CAEP\'s Likelihood Normalization......Page 46
  Emerging Pattern Set Selection......Page 47
 A Small Illustrating Example......Page 48
 Experiments and Applications by Other Researchers......Page 49
  Strengths of CAEP......Page 50
 DeEPs: Instance-Based Classification Using Emerging Patterns......Page 51
 Relationship with Other Rule/Pattern-Based Classifiers......Page 52
 Discussion......Page 53
 CAEP Performs Well on Tiny Training Data......Page 54
  Details on Data Used for Compound Selection......Page 55
 Using CAEP for Compound Selection......Page 56
 Semi-Supervised Extreme Instance Selection vs. Semi-Supervised Learning......Page 57
 Background on Intrusion Detection, Anomaly Detection, and Outlier Detection......Page 60
  An Observation on Emerging Pattern\'s Length......Page 61
  What Emerging Patterns to Use and Their Mining......Page 62
  OCLEP\'s Training and Testing Algorithms......Page 63
 Experimental Evaluation of OCLEP......Page 64
  Masquerader Detection on Command Sequences......Page 65
 Discussion......Page 66
 Background on Clustering-Quality Evaluation......Page 68
 Measuring Quality of CPs......Page 69
 Measuring Diversity of High-Quality CPs......Page 70
 Defining CPCQ......Page 71
 Mining CPs and Computing the Best N Groups of CPs to Maximize CPCQ Values......Page 72
 Discussion......Page 73
 Background on Clustering and Clustering Evaluation......Page 74
 Problem Setting and Guiding Ideas for CPC......Page 75
  MPQ Between Two Patterns......Page 76
  MPQ Between a Pattern and a Pattern Set......Page 77
 The CPC Algorithm......Page 78
 General Experimental Evaluation of CPC......Page 79
 Text Data Analysis on Blogs Using CPC......Page 80
 Discussion......Page 81
IBIG: Ranking Genes and Attributes for Complex Diseases and Complex Problems......Page 82
 Basics of the Gene-Ranking Problem......Page 83
 Background on Complex Diseases......Page 84
 Capturing Interactions Using Jumping Emerging Patterns......Page 85
  IBIG Gene Ranking based on a Set of Emerging Patterns......Page 86
  Gene Clubs and Computing Gene Clubs......Page 87
 Experimental Findings on IBIG on Colon Cancer Data......Page 88
  Significant Gene-Rank Differences Between IG and IBIG......Page 89
 Discussion......Page 90
 Background Materials......Page 94
  Fitting Local Models for Logical Subpopulations......Page 95
  Pattern Aided Prediction Models......Page 96
 CPXP: Contrast Pattern Aided Prediction......Page 97
 Diverse Predictor-Response Relationships......Page 99
  Experiments on Commonly Used Datasets......Page 100
  Applications for Agriculture and Healthcare Predictions......Page 101
 Subpopulationwise Conditional Correlation Analysis......Page 102
 Discussion......Page 103
 Compound Activity Analysis......Page 104
 Metabolite Biomarker Discovery......Page 105
 Safety and Street Crime Analysis......Page 106
 Identifying Interaction Terms: Adverse Drug Reaction Analysis......Page 107
 Protein Complex Detection......Page 108
 Inhibitor Prediction Combining FCA and JEP......Page 109
 Surgery Stage Identification and Feedback Delivery......Page 110
 Other EP-based Classification Approaches and Studies......Page 111
 Other Studies and Applications......Page 113
 Summary of Uses: Application Domain Perspective......Page 115
 Discussion......Page 116
Bibliography......Page 118
Author\'s Biography......Page 0
Index......Page 144