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Emerging patterns are sets of items whose frequency changes significantly from one dataset to another. They are useful as a means of discovering distinctions inherently present amongst a collection datasets and have been shown to be a powerful method for constructing accurate classifiers. In this paper, we present different varieties of emerging patterns, discuss efficient techniques for their discovery and explain how they can be used in classification.