Reference change · 10.1007/s10618-025-01132-4

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Improving Multivariate Time Series Classification with Class-Wise Training and Model Aggregation

ref [13] · 2609.07493 · notice #10955 · dispute

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imental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery38(4), 1958-2031 (2024).https://doi.org/10.1007/ s10618-024-01022-1 13. Nuyts, L., Perini, L., Davis, J.: Tselect: Selecting relevant and non-redundant chan- nels for multivariate time series classification. Data Mining and Knowledge Dis- covery39(6), 76 (2025).https://doi.org/10.1007/s10618-025-01132-4 14. Ruiz, A.P., Flynn, M., Large, J., Middlehurst, M., Bagnall, A.: The great multi- variate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data mining and knowledge discovery35(2), 401-449 (2021).https://doi.org/10.1007/s10618-020-00727-3 15. Schäfer, P., Leser, U.: Multivariate time series classification with weasel+muse.

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imental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery38(4), 1958-2031 (2024).https://doi.org/10.1007/ s10618-024-01022-1 13. Nuyts, L., Perini, L., Davis, J.: Tselect: Selecting relevant and non-redundant chan- nels for multivariate time series classification. Data Mining and Knowledge Dis- covery39(6), 76 (2025).https://doi.org/10.1007/s10618-025-01132-4 14. Ruiz, A.P., Flynn, M., Large, J., Middlehurst, M., Bagnall, A.: The great multi- variate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data mining and knowledge discovery35(2), 401-449 (2021).https://doi.org/10.1007/s10618-020-00727-3 15. Schäfer, P., Leser, U.: Multivariate time series classification with weasel+muse

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