Tony Bagnall
Tony Bagnall
Professor of Computer Science, University of East Anglia
Verified email at - Homepage
Cited by
Cited by
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 (3), 606-660, 2017
The ucr time series classification archive
Y Chen, E Keogh, B Hu, N Begum, A Bagnall, A Mueen, G Batista
July, 2015
The next release problem
AJ Bagnall, VJ Rayward-Smith, IM Whittley
Information and software technology 43 (14), 883-890, 2001
Classification of time series by shapelet transformation
J Hills, J Lines, E Baranauskas, J Mapp, A Bagnall
Data mining and knowledge discovery 28 (4), 851-881, 2014
Time-series classification with COTE: the collective of transformation-based ensembles
A Bagnall, J Lines, J Hills, A Bostrom
IEEE Transactions on Knowledge and Data Engineering 27 (9), 2522-2535, 2015
Time series classification with ensembles of elastic distance measures
J Lines, A Bagnall
Data Mining and Knowledge Discovery 29 (3), 565-592, 2015
A shapelet transform for time series classification
J Lines, LM Davis, J Hills, A Bagnall
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
The UCR time series archive
HA Dau, A Bagnall, K Kamgar, CCM Yeh, Y Zhu, S Gharghabi, ...
IEEE/CAA Journal of Automatica Sinica 6 (6), 1293-1305, 2019
A novel bit level time series representation with implication of similarity search and clustering
C Ratanamahatana, E Keogh, AJ Bagnall, S Lonardi
Pacific-Asia conference on knowledge discovery and data mining, 771-777, 2005
Time series classification with HIVE-COTE: The hierarchical vote collective of transformation-based ensembles
J Lines, S Taylor, A Bagnall
ACM Transactions on Knowledge Discovery from Data 12 (5), 2018
A multiagent model of the UK market in electricity generation
AJ Bagnall, GD Smith
IEEE Transactions on Evolutionary Computation 9 (5), 522-536, 2005
Transformation based ensembles for time series classification
A Bagnall, L Davis, J Hills, J Lines
Proceedings of the 2012 SIAM international conference on data mining, 307-318, 2012
Clustering time series from ARMA models with clipped data
AJ Bagnall, GJ Janacek
Proceedings of the tenth ACM SIGKDD international conference on knowledge …, 2004
Clustering time series with clipped data
A Bagnall, G Janacek
Machine learning 58 (2-3), 151-178, 2005
A bit level representation for time series data mining with shape based similarity
A Bagnall, E Keogh, S Lonardi, G Janacek
Data Mining and Knowledge Discovery 13 (1), 11-40, 2006
Hive-cote: The hierarchical vote collective of transformation-based ensembles for time series classification
J Lines, S Taylor, A Bagnall
2016 IEEE 16th international conference on data mining (ICDM), 1041-1046, 2016
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
Data mining rules using multi-objective evolutionary algorithms
B De La Iglesia, MS Philpott, AJ Bagnall, VJ Rayward-Smith
The 2003 Congress on Evolutionary Computation, 2003. CEC'03. 3, 1552-1559, 2003
The UEA & UCR time series classification repository
A Bagnall, J Lines, W Vickers, E Keogh
URL http://www. timeseriesclassification. com, 2018
Classification of household devices by electricity usage profiles
J Lines, A Bagnall, P Caiger-Smith, S Anderson
International conference on intelligent data engineering and automated …, 2011
The system can't perform the operation now. Try again later.
Articles 1–20