Abstract
Jumping Emerging Patterns (JEP) are patterns that only occur in objects of a single class, a minimal JEP is a JEP where none of its proper subsets is a JEP. In this paper, an efficient method to mine the whole set of the minimal JEPs is detailed and fully proven. Moreover, our method has a larger scope since it is able to compute the essential JEPs and the top-k minimal JEPs. We also extract minimal JEPs where the absence of attributes is stated, and we show that this leads to the discovery of new valuable pieces of information. A performance study is reported to evaluate our approach and the practical efficiency of minimal JEPs in the design of rules to express correlations is shown.
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Kane, B., Cuissart, B., Crémilleux, B. (2015). Minimal Jumping Emerging Patterns: Computation and Practical Assessment. In: Cao, T., Lim, EP., Zhou, ZH., Ho, TB., Cheung, D., Motoda, H. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2015. Lecture Notes in Computer Science(), vol 9077. Springer, Cham. https://doi.org/10.1007/978-3-319-18038-0_56
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DOI: https://doi.org/10.1007/978-3-319-18038-0_56
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