A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0
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Abstract (arXiv)
The Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) is a heterogeneous meta ensemble for time series classification. Since it was first proposed in 2016, the algorithm has undergone some minor changes and there is now a configurable, scalable and easy to use version available in two open source repositories. We present an overview of the latest stable HIVE-COTE, version 1.0, and describe how it differs to the original. We provide a walkthrough guide of how to use the classifier, and conduct extensive experimental evaluation of its predictive performance and resource usage. We compare the performance of HIVE-COTE to three recently proposed algorithms using the aeon toolkit.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Apr 2020.
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Citing papers per year: 2021: 7; 2022: 1; 2023: 3; 2024: 1.
12 papers.
- 2021HIVE-COTE 2.0: a new meta ensemble for time series classificationcited by 118
- 2023Bake off redux: a review and experimental evaluation of recent time series classification algorithmscited by 99
- 2021MultiRocket: Multiple pooling operators and transformations for fast and effective time series classificationcited by 89
- 2021The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classificationcited by 26
- 2022The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifiercited by 18
- 2021Elastic Similarity and Distance Measures for Multivariate Time Seriescited by 8
- 2021MrSQM: Fast Time Series Classification with Symbolic Representationscited by 7
- 2023Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithmscited by 7
- 2021Fast, Accurate and Interpretable Time Series Classification Through Randomizationcited by 5
- 2021Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warpingcited by 3
- 2023FedST: Secure Federated Shapelet Transformation for Time Series Classificationcited by 1
- 2024Contrast Similarity-Aware Dual-Pathway Mamba for Multivariate Time Series Node Classificationcited by 0
- 2024Contrast Similarity-Aware Dual-Pathway Mamba for Multivariate Time Series Node Classification19 Nov 2024
- 2023Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithms4 Oct 2023
- 2023Bake off redux: a review and experimental evaluation of recent time series classification algorithms25 Apr 2023
- 2023FedST: Secure Federated Shapelet Transformation for Time Series Classification21 Feb 2023
- 2022The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier28 Jan 2022
- 2021MrSQM: Fast Time Series Classification with Symbolic Representations2 Sep 2021
- 2021Fast, Accurate and Interpretable Time Series Classification Through Randomization31 May 2021
- 2021The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification9 May 2021
- 2021HIVE-COTE 2.0: a new meta ensemble for time series classification15 Apr 2021
- 2021Elastic Similarity and Distance Measures for Multivariate Time Series20 Feb 2021
- 2021Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping10 Feb 2021
- 2021MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification31 Jan 2021