Significance-based interpretable sequence clustering

Zengyou He, Lianyu Hu, Jinfeng He, Junjie Dong, Mudi Jiang, Xinying Liu

Abstract: Highlights•SigISC is the first significance-based interpretable clustering method for sequences.•SigISC proposes a new cluster-critical pattern mining algorithm.•Experiments show SigISC achieve comparable performance to state-of-the-art methods.