mlsanityData to 7 Oct 2026

HIVE-COTE 2.0: a new meta ensemble for time series classification

arXiv 2104.07551 ↗First posted 15 Apr 2021cs.LGcited by 118

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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. HIVE-COTE forms its ensemble from classifiers of multiple domains, including phase-independent shapelets, bag-of-words based dictionaries and phase-dependent intervals. Since it was first proposed in 2016, the algorithm has remained state of the art for accuracy on the UCR time series classification archive. Over time it has been incrementally updated, culminating in its current state, HIVE-COTE 1.0. During this time a number of algorithms have been proposed which match the accuracy of HIVE-COTE. We propose comprehensive changes to the HIVE-COTE algorithm which significantly improve its accuracy and usability, presenting this upgrade as HIVE-COTE 2.0. We introduce two novel classifiers, the Temporal Dictionary Ensemble (TDE) and Diverse Representation Canonical Interval Forest (DrCIF), which replace existing ensemble members. Additionally, we introduce the Arsenal, an ensemble of ROCKET classifiers as a new HIVE-COTE 2.0 constituent. We demonstrate that HIVE-COTE 2.0 is significantly more accurate than the current state of the art on 112 univariate UCR archive datasets and 26 multivariate UEA archive datasets.

Key facts. Cited by 118 papers in the map (data through 7 Oct 2026). Builds on 22 of its 47 references that are in the map. First posted on arXiv 15 Apr 2021.

Builds on

22 of 47 references.

References · 22

  1. 2014Going Deeper with Convolutionscited by 4,231
  2. 2018Deep learning for time series classification: a reviewcited by 575
  3. 2018The UCR Time Series Archivecited by 421
  4. 2019InceptionTime: Finding AlexNet for Time Series Classificationcited by 386
  5. 2019ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernelscited by 336
  6. 2018The UEA multivariate time series classification archive, 2018cited by 330
  7. 2020Benchmarking Multivariate Time Series Classification Algorithmscited by 145
  8. 2015Should we really use post-hoc tests based on mean-ranks?cited by 116
  9. 2019catch22: CAnonical Time-series CHaracteristicscited by 103
  10. 2013A Time Series Forest for Classification and Feature Extractioncited by 69
  11. 2019TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classificationcited by 67
  12. 2017Multivariate Time Series Classification with WEASEL+MUSEcited by 53
10 more
  1. 2020The Canonical Interval Forest (CIF) Classifier for Time Series Classificationcited by 48
  2. 2017Fast and Accurate Time Series Classification with WEASELcited by 47
  3. 2018Proximity Forest: An effective and scalable distance-based classifier for time seriescited by 46
  4. 2020Interpretable Time Series Classification using Linear Models and Multi-resolution Multi-domain Symbolic Representationscited by 31
  5. 2019Scalable Dictionary Classifiers for Time Series Classificationcited by 20
  6. 2018From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifierscited by 14
  7. 2016Automatic time-series phenotyping using massive feature extractioncited by 12
  8. 2020A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0cited by 12
  9. 2020Applications of shapelet transform to time series classification of earthquake, wind and wave datacited by 8
  10. 2017The Heterogeneous Ensembles of Standard Classification Algorithms (HESCA): the Whole is Greater than the Sum of its Partscited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 13; 2023: 38; 2024: 24; 2025: 20; 2026: 20.

118 papers.

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  1. 2023A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detectioncited by 145
  2. 2023Bake off redux: a review and experimental evaluation of recent time series classification algorithmscited by 99
  3. 2023Deep Learning for Time Series Classification and Extrinsic Regression: A Current Surveycited by 68
  4. 2022HYDRA: Competing convolutional kernels for fast and accurate time series classificationcited by 53
  5. 2023LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation -- Extended Versioncited by 49
  6. 2024aeon: a Python toolkit for learning from time seriescited by 46
  7. 2023Improving Position Encoding of Transformers for Multivariate Time Series Classificationcited by 44
  8. 2023An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Setcited by 27
  9. 2024ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysiscited by 26
  10. 2023Inherently Interpretable Time Series Classification via Multiple Instance Learningcited by 23
  11. 2021Random Dilated Shapelet Transform: A New Approach for Time Series Shapeletscited by 22
  12. 2022Dynamic Sparse Network for Time Series Classification: Learning What to "see''cited by 22
38 more
  1. 2023FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classificationcited by 21
  2. 2023NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretrainingcited by 20
  3. 2022The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifiercited by 18
  4. 2023WEASEL 2.0 -- A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series Classificationcited by 15
  5. 2023QUANT: A Minimalist Interval Method for Time Series Classificationcited by 15
  6. 2022A Review and Evaluation of Elastic Distance Functions for Time Series Clusteringcited by 14
  7. 2022HDC-MiniROCKET: Explicit Time Encoding in Time Series Classification with Hyperdimensional Computingcited by 13
  8. 2024From Variability to Stability: Advancing RecSys Benchmarking Practicescited by 12
  9. 2025Learning Soft Sparse Shapes for Efficient Time-Series Classificationcited by 10
  10. 2023Unsupervised Feature Based Algorithms for Time Series Extrinsic Regressioncited by 9
  11. 2024Look Into the LITE in Deep Learning for Time Series Classificationcited by 9
  12. 2023Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fieldscited by 8
  13. 2024Exploring Kolmogorov-Arnold Networks for Interpretable Time Series Classificationcited by 8
  14. 2024TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Modelscited by 8
  15. 2024On the Feasibility of Vision-Language Models for Time-Series Classificationcited by 8
  16. 2021MrSQM: Fast Time Series Classification with Symbolic Representationscited by 7
  17. 2022Neuro-symbolic Models for Interpretable Time Series Classification using Temporal Logic Descriptioncited by 7
  18. 2022POPNASv3: a Pareto-Optimal Neural Architecture Search Solution for Image and Time Series Classificationcited by 7
  19. 2023Appliance Detection Using Very Low-Frequency Smart Meter Time Seriescited by 7
  20. 2023MTS2Graph: Interpretable Multivariate Time Series Classification with Temporal Evolving Graphscited by 7
  21. 2023Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelscited by 7
  22. 2023Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithmscited by 7
  23. 2024QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models -- Extended Versioncited by 7
  24. 2021Multi-Stage Prototype Learning for Interpretable Time Series Classificationcited by 6
  25. 2025MONSTER: Monash Scalable Time Series Evaluation Repositorycited by 6
  26. 2022Rethinking Attention Mechanism in Time Series Classificationcited by 5
  27. 2023Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time seriescited by 5
  28. 2025MASCOTS: Model-Agnostic Symbolic COunterfactual explanations for Time Seriescited by 5
  29. 2023POCKET: Pruning Random Convolution Kernels for Time Series Classification from a Feature Selection Perspectivecited by 4
  30. 2023Finding Foundation Models for Time Series Classification with a PreText Taskcited by 4
  31. 2023ADF & TransApp: A Transformer-Based Framework for Appliance Detection Using Smart Meter Consumption Seriescited by 4
  32. 2025Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecastingcited by 4
  33. 2026RocketPFN: Accurate Time Series Classification via In-Context Learningcited by 4
  34. 2023Parameterizing the cost function of Dynamic Time Warping with application to time series classificationcited by 3
  35. 2023RED CoMETS: An ensemble classifier for symbolically represented multivariate time seriescited by 3
  36. 2023Automatic Feature Engineering for Time Series Classification: Evaluation and Discussioncited by 3
  37. 2024Data Augmentation for Multivariate Time Series Classification: An Experimental Studycited by 3
  38. 2026The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classificationcited by 3

50 most cited of 118 All 118 (JSON)