Mining Top-k Relevant Patterns using Minimum Support Raising
最小サポート上昇法に基づく上位k 関連パターン発見

Yoshitaka KAMEYA, Taisuke SATO
JSAI Technical Report, Type 2 SIG  
One practical inconvenience in frequent pattern mining is that it often yields a flood of common or uninformative patterns, and thus we should carefully adjust the minimum support. To alleviate this inconvenience, based on FP-growth, this paper proposes RP-growth, an efficient algorithm for top-k mining of discriminative patterns which are highly relevant to the class of interest. RP-growth conducts a branch-and-bound search using anti-monotonic upper bounds of the relevance scores such as
more » ... re and χ 2 , and the pruning in branch-and-bound search is successfully translated to minimum support raising, a standard, easy-to-implement pruning strategy for top-k mining. Furthermore, by introducing the notion of weakness and an additional, aggressive pruning strategy based on weakness, RP-growth efficiently find k patterns of wide variety and high relevance to the class of interest.
doi:10.11517/jsaisigtwo.2011.docmas-b101_04 fatcat:tipvelb6lfh5diwfaljqskbp3e