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TIGER: Time-Series Classification with In-Context-Learning Gated Ensemble of Representations
A representation family is a distinct way of extracting features from time series. Ensemble algorithms that combine several representation families remain the most accurate approach to time series classification. Current state-of-the-art ensembles, most notably HIVE-COTE~2.0, pair a bespoke classifi
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