Time Series data Mining Using the Matrix Profile: A Unifying View of Motif Discovery, Anomaly Detection, Segmentation, Classification, Clustering and Similarity Joins
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The Matrix Profile (and the algorithms to compute it: STAMP, STAMPI, STOMP, SCRIMP and GPU-STOMP), has the potential to revolutionize time series data mining because of its generality, versatility, simplicity and scalability. In particular it has implications for time series motif discovery, time series joins, shapelet discovery (classification), density estimation, semantic segmentation, visualization, clustering etc.
Link to tutorial: http://www.cs.ucr.edu/~eamonn/MatrixProfile.html
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