Grosskreutz, HenrikHenrikGrosskreutz2022-03-122022-03-122012https://publica.fraunhofer.de/handle/publica/379207The set of so-called relevant patterns is a subset of all itemsets particularly suited for pattern-based classifica- Tion tasks. So far, no efficient algorithm has been de- veloped for computing the set of relevant patterns: All existing solutions have a worst-case complexity which is exponential in the size of the input and output. In this paper, we investigate new properties of the relevant pat- Terns and develop, thereupon, the first algorithm whose runtime is polynomial in the size of the input and out- put. As we show in the experimental section, this result is not only of theoretical interest but also of practical importance, often reducing the search space by orders of magnitude.en005Class relevant pattern mining in output-polynomial timeconference paper