ABSTRACT
Emerging patterns (EPs) are itemsets whose supports increase significantly from one dataset to another. EPs can capture emerging trends in timestamped databases, or useful contrasts between data classes. In this chapter, we introduce three applications of EPs: prediction of myocardial ischemia (MI), coronary artery disease (CAD) diagnosis, and classification of powerline safety. We present the background of these three applications, the classification problems, the important features, and how to prepare the data for mining EPs. We also give some EPs examples for these applications.
