| The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances A Bagnall, J Lines, A Bostrom, J Large, E Keogh Data mining and knowledge discovery 31, 606-660, 2017 | 1891 | 2017 |
| The UEA multivariate time series classification archive, 2018 A Bagnall, HA Dau, J Lines, M Flynn, J Large, A Bostrom, P Southam, ... arXiv preprint arXiv:1811.00075, 2018 | 549 | 2018 |
| The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances AP Ruiz, M Flynn, J Large, M Middlehurst, A Bagnall Data Mining and Knowledge Discovery 35 (2), 401-449, 2021 | 490 | 2021 |
| HIVE-COTE 2.0: a new meta ensemble for time series classification M Middlehurst, J Large, M Flynn, J Lines, A Bostrom, A Bagnall Machine Learning 110 (11), 3211-3243, 2021 | 286 | 2021 |
| The canonical interval forest (CIF) classifier for time series classification M Middlehurst, J Large, A Bagnall 2020 IEEE international conference on big data (big data), 188-195, 2020 | 149 | 2020 |
| The temporal dictionary ensemble (TDE) classifier for time series classification M Middlehurst, J Large, G Cawley, A Bagnall Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 107 | 2021 |
| A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates J Large, J Lines, A Bagnall Data mining and knowledge discovery 33 (6), 1674-1709, 2019 | 88 | 2019 |
| On time series classification with dictionary-based classifiers J Large, A Bagnall, S Malinowski, R Tavenard Intelligent Data Analysis 23 (5), 1073-1089, 2019 | 72 | 2019 |
| On the usage and performance of the hierarchical vote collective of transformation-based ensembles version 1.0 (hive-cote v1. 0) A Bagnall, M Flynn, J Large, J Lines, M Middlehurst Advanced Analytics and Learning on Temporal Data: 5th ECML PKDD Workshop …, 2020 | 67 | 2020 |
| The contract random interval spectral ensemble (c-RISE): The effect of contracting a classifier on accuracy M Flynn, J Large, T Bagnall Hybrid Artificial Intelligent Systems: 14th International Conference, HAIS …, 2019 | 65 | 2019 |
| Is rotation forest the best classifier for problems with continuous features? A Bagnall, M Flynn, J Large, J Line, A Bostrom, G Cawley arXiv preprint arXiv:1809.06705, 2018 | 49 | 2018 |
| A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1. 0 A Bagnall, M Flynn, J Large, J Lines, M Middlehurst arXiv preprint arXiv:2004.06069, 2020 | 29 | 2020 |
| Detecting forged alcohol non-invasively through vibrational spectroscopy and machine learning J Large, EK Kemsley, N Wellner, I Goodall, A Bagnall Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia …, 2018 | 27 | 2018 |
| The heterogeneous ensembles of standard classification algorithms (HESCA): the whole is greater than the sum of its parts J Large, J Lines, A Bagnall arXiv preprint arXiv:1710.09220, 2017 | 21 | 2017 |
| Simulated data experiments for time series classification Part 1: accuracy comparison with default settings A Bagnall, A Bostrom, J Large, J Lines arXiv preprint arXiv:1703.09480, 2017 | 21 | 2017 |
| From BOP to BOSS and beyond: Time series classification with dictionary based classifiers J Large, A Bagnall, S Malinowski, R Tavenard arXiv preprint arXiv:1809.06751, 2018 | 15 | 2018 |
| Can automated smoothing significantly improve benchmark time series classification algorithms? J Large, P Southam, A Bagnall Hybrid Artificial Intelligent Systems: 14th International Conference, HAIS …, 2019 | 5 | 2019 |
| alan-turing-institute/sktime: v0. 10.1 M Löning, T Bagnall, M Middlehurst, F Király, S Ganesh, G Oastler, ... Zenodo, 2022 | 3 | 2022 |
| A tale of two toolkits, report the second: bake off redux. chapter 1. dictionary based classifiers A Bagnall, J Large, M Middlehurst arXiv preprint arXiv:1911.12008, 2019 | 2 | 2019 |
| „The great time series classification bake off,“ A Bagnall, J Lines, A Bostrom, J Large, E Keogh Data Mining and Knowledge Discovery, 606-660, 2016 | 2 | 2016 |
Tony BagnallProfessor of Computer Science, University of SouthamptonПодтвержден адрес электронной почты в домене uea.ac.uk