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Bibliographic Details
Main Authors:	Lo, Mouhamadou Mansour, Morvan, Gildas, Rossi, Mathieu, Morganti, Fabrice, Mercier, David
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2409.01115
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This article presents a new approach based on MiniRocket, called SelF-Rocket, for fast time series classification (TSC). Unlike existing approaches based on random convolution kernels, it dynamically selects the best couple of input representations and pooling operator during the training process. SelF-Rocket achieves state-of-the-art accuracy on the University of California Riverside (UCR) TSC benchmark datasets.