An Interpretable Baseline for Time Series Classification Without Intensive Learning

13 Jul 2020Robert J. RavierMohammadreza SoltaniMiguel Antunes Dias AlfaiateDenis GaragicVahid Tarokh

Recent advances in time series classification have largely focused on methods that either employ deep learning or utilize other machine learning models for feature extraction. Though such methods have proven powerful, they can also require computationally expensive models that may lack interpretability of results, or may require larger datasets than are freely available... (read more)

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