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The Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) is a heterogeneous meta ensemble for time series classification.
Fawaz H, Lucas B, Forestier G, Pelletier C, Schmidt D, Weber J, Webb G, Idoumghar L, Muller P, Petitjean F (2020) InceptionTime: finding AlexNet for time series classification. Data Mining and Knowledge Discovery 34(6):1936–1962
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Lines J, Taylor S, Bagnall A (2016) HIVE-COTE: The hierarchical vote collective of transformation-based ensembles for time series classification. In: proceedings of 16th IEEE International Conference on Data Mining
Fawaz H, Forestier G, Weber J, Idoumghar L, Muller P (2019) Deep learning for time series classification: a review. Data Mining and Knowledge Discovery 33(4):917–963
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Bagnall A, Lines J, Bostrom A, Large J, Keogh E (2017) The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery 31(3):606–660
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Bagnall A, Flynn M, Large J, Lines J, Middlehurst M (2020) On the usage and performance of HIVE-COTE v1.0. In: proceedings of the 5th Workshop on Advances Analytics and Learning on Temporal Data, Lecture Notes in Artificial Intelligence, vol 12588
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Arul M, Kareem A (2021) Applications of shapelet transform to time series classification of earthquake, wind and wave data. Engineering Structures 228:111564
2021
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Ruiz AP, Flynn M, Large J, Middlehurst M, Bagnall A (2021) The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery 35(2):401––449
2021
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