Generalized random shapelet forests

• Published in: Data mining and knowledge discovery Vol. 30; no. 5; pp. 1053 - 1085
• Main Authors: Karlsson, Isak, Papapetrou, Panagiotis, Boström, Henrik
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2016; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Chemistry and Earth Sciences; Computation; Computer and Systems Sciences; Computer Science; Data mining; Data Mining and Knowledge Discovery; data- och systemvetenskap; Datasets; Decision trees; Electrocardiography; Ensemble methods; Forests; Information Storage and Retrieval; Learning; Multivariate time series; Physics; State of the art; Statistics for Engineering; Time series; Time series classification; Time series shapelets; Variables; Multivariate time series; Ensemble methods; Decision trees; Time series classification; Time series shapelets

Shapelets are discriminative subsequences of time series, usually embedded in shapelet-based decision trees. The enumeration of time series shapelets is, however, computationally costly, which in addition to the inherent difficulty of the decision tree learning algorithm to effectively handle high-d...