Efficiently Mining Interesting Emerging Patterns

Emerging patterns (EPs) are itemsets whose supports change significantly from one class to another. It has been shown that they are very powerful distinguishable features and they are very useful for constructing accurate classifiers. Previous EP mining approaches often produce a large number of EPs, which makes it very difficult to choose interesting ones manually. Usually, a post-processing filter step is applied for selecting interesting EPs based on some interestingness measures.

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