Anthony J. Bagnall

ORCID

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 69

Top Venues

CoRR

Data Min. Knowl. Discov.

AALTD@ECML/PKDD

IDEAL (1)

Publications

Anthony J. Bagnall, Matthew Middlehurst, Germain Forestier, Ali Ismail-Fawaz, Antoine Guillaume, David Guijo-Rubio, Chang Wei Tan, Angus Dempster, Geoffrey I. Webb
A Hands-on Introduction to Time Series Classification and Regression. KDD (2024)
Christopher Holder, Matthew Middlehurst, Anthony J. Bagnall
A review and evaluation of elastic distance functions for time series clustering. Knowl. Inf. Syst. 66 (2) (2024)
Matthew Middlehurst, Ali Ismail-Fawaz, Antoine Guillaume, Christopher Holder, David Guijo-Rubio, Guzal Bulatova, Leonidas Tsaprounis, Lukasz Mentel, Martin Walter, Patrick Schäfer, Anthony J. Bagnall
aeon: a Python toolkit for learning from time series. CoRR (2024)
David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio, Diego Furtado Silva, Anthony J. Bagnall
Unsupervised feature based algorithms for time series extrinsic regression. Data Min. Knowl. Discov. 38 (4) (2024)
Matthew Middlehurst, Patrick Schäfer, Anthony J. Bagnall
Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Min. Knowl. Discov. 38 (4) (2024)
Aiden Rushbrooke, Jordan Tsigarides, Saber Sami, Anthony J. Bagnall
Time Series Classification of Electroencephalography Data. IWANN (1) (2023)
Rafael Ayllón-Gavilán, David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony J. Bagnall, César Hervás-Martínez
Convolutional and Deep Learning based techniques for Time Series Ordinal Classification. CoRR (2023)
Matthew Middlehurst, Patrick Schäfer, Anthony J. Bagnall
Bake off redux: a review and experimental evaluation of recent time series classification algorithms. CoRR (2023)
Matthew Middlehurst, Anthony J. Bagnall
Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression. AALTD@ECML/PKDD (2023)
Arik Ermshaus, Patrick Schäfer, Anthony J. Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski
Human Activity Segmentation Challenge @ ECML/PKDD'23. AALTD@ECML/PKDD (2023)
David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio, Diego Furtado Silva, Anthony J. Bagnall
Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression. CoRR (2023)
Christopher Holder, David Guijo-Rubio, Anthony J. Bagnall
Barycentre Averaging for the Move-Split-Merge Time Series Distance Measure. KDIR (2023)
Christopher Holder, David Guijo-Rubio, Anthony J. Bagnall
Clustering Time Series with k-Medoids Based Algorithms. AALTD@ECML/PKDD (2023)
Matthew Middlehurst, Anthony J. Bagnall
The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier. CoRR (2022)
Alejandro Pasos Ruiz, Anthony J. Bagnall
Dimension Selection Strategies for Multivariate Time Series Classification with HIVE-COTEv2.0. AALTD@ECML/PKDD (2022)
Matthew Middlehurst, Anthony J. Bagnall
The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier. ICPRAI (2) (2022)
Chris Holder, Matthew Middlehurst, Anthony J. Bagnall
A Review and Evaluation of Elastic Distance Functions for Time Series Clustering. CoRR (2022)
Matthew Middlehurst, James Large, Gavin C. Cawley, Anthony J. Bagnall
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. CoRR (2021)
Matthew Middlehurst, James Large, Michael Flynn, Jason Lines, Aaron Bostrom, Anthony J. Bagnall
HIVE-COTE 2.0: a new meta ensemble for time series classification. Mach. Learn. 110 (11) (2021)
Alejandro Pasos Ruiz, Michael Flynn, James Large, Matthew Middlehurst, Anthony J. Bagnall
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Discov. 35 (2) (2021)
Matthew Middlehurst, James Large, Michael Flynn, Jason Lines, Aaron Bostrom, Anthony J. Bagnall
HIVE-COTE 2.0: a new meta ensemble for time series classification. CoRR (2021)
Matthew Middlehurst, James Large, Anthony J. Bagnall
The Canonical Interval Forest (CIF) Classifier for Time Series Classification. IEEE BigData (2020)
Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
An ultra-fast time series distance measure to allow data mining in more complex real-world deployments. Data Min. Knowl. Discov. 34 (4) (2020)
Alejandro Pasos Ruiz, Michael Flynn, Anthony J. Bagnall
Benchmarking Multivariate Time Series Classification Algorithms. CoRR (2020)
David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony J. Bagnall, César Hervás-Martínez
Ordinal Versus Nominal Time Series Classification. AALTD@PKDD/ECML (2020)
Thakolpat Khampuengson, Anthony J. Bagnall, Wenjia Wang
Developing Ensemble Methods for Detecting Anomalies in Water Level Data. SGAI Conf. (2020)
Anthony J. Bagnall, Michael Flynn, James Large, Jason Lines, Matthew Middlehurst
A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0. CoRR (2020)
Matthew Middlehurst, James Large, Anthony J. Bagnall
The Canonical Interval Forest (CIF) Classifier for Time Series Classification. CoRR (2020)
Anthony J. Bagnall, Michael Flynn, James Large, Jason Lines, Matthew Middlehurst
On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0). AALTD@PKDD/ECML (2020)
Anthony J. Bagnall, Paul Southam, James Large, Richard W. Harvey
Detecting Electric Devices in 3D Images of Bags. CoRR (2020)
Matthew Middlehurst, James Large, Gavin C. Cawley, Anthony J. Bagnall
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. ECML/PKDD (1) (2020)
David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony J. Bagnall, César Hervás-Martínez
Time series ordinal classification via shapelets. IJCNN (2020)
Matthew Middlehurst, William Vickers, Anthony J. Bagnall
Scalable Dictionary Classifiers for Time Series Classification. CoRR (2019)
Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
The UCR time series archive. IEEE CAA J. Autom. Sinica 6 (6) (2019)
James Large, Jason Lines, Anthony J. Bagnall
A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates. Data Min. Knowl. Discov. 33 (6) (2019)
James Large, Paul Southam, Anthony J. Bagnall
Can Automated Smoothing Significantly Improve Benchmark Time Series Classification Algorithms? HAIS (2019)
Anthony J. Bagnall, James Large, Matthew Middlehurst
A tale of two toolkits, report the second: bake off redux. Chapter 1. dictionary based classifiers. CoRR (2019)
Anthony J. Bagnall, Franz J. Király, Markus Löning, Matthew Middlehurst, George Oastler
A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency. CoRR (2019)
James Large, Anthony J. Bagnall
Mixing Hetero- and Homogeneous Models in Weighted Ensembles. IDEAL (1) (2019)
James Large, Anthony J. Bagnall, Simon Malinowski, Romain Tavenard
On time series classification with dictionary-based classifiers. Intell. Data Anal. 23 (5) (2019)
David Guijo-Rubio, Pedro Antonio Gutiérrez, Romain Tavenard, Anthony J. Bagnall
A Hybrid Approach to Time Series Classification with Shapelets. IDEAL (1) (2019)
Michael Flynn, Anthony J. Bagnall
Classifying Flies Based on Reconstructed Audio Signals. IDEAL (2) (2019)
Anthony J. Bagnall, Richard L. Cole, Themis Palpanas, Konstantinos Zoumpatianos
Data Series Management (Dagstuhl Seminar 19282). Dagstuhl Reports 9 (7) (2019)
Markus Löning, Anthony J. Bagnall, Sajaysurya Ganesh, Viktor Kazakov, Jason Lines, Franz J. Király
sktime: A Unified Interface for Machine Learning with Time Series. CoRR (2019)
Matthew Middlehurst, William Vickers, Anthony J. Bagnall
Scalable Dictionary Classifiers for Time Series Classification. IDEAL (1) (2019)
Anthony J. Bagnall, Aaron Bostrom, Gavin C. Cawley, Michael Flynn, James Large, Jason Lines
Is rotation forest the best classifier for problems with continuous features? CoRR (2018)
Jason Lines, Sarah Taylor, Anthony J. Bagnall
Time Series Classification with HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles. ACM Trans. Knowl. Discov. Data 12 (5) (2018)
James Large, Anthony J. Bagnall, Simon Malinowski, Romain Tavenard
From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers. CoRR (2018)
James Large, E. Kate Kemsley, Nikolaus Wellner, Ian Goodall, Anthony J. Bagnall
Detecting Forged Alcohol Non-invasively Through Vibrational Spectroscopy and Machine Learning. PAKDD (1) (2018)
Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Abdullah Mueen, Eamonn J. Keogh
Optimizing dynamic time warping's window width for time series data mining applications. Data Min. Knowl. Discov. 32 (4) (2018)
Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios. ICDM (2018)
Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
The UCR Time Series Archive. CoRR (2018)
Anthony J. Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, Eamonn J. Keogh
The UEA multivariate time series classification archive, 2018. CoRR (2018)
James Large, Paul Southam, Anthony J. Bagnall
Can automated smoothing significantly improve benchmark time series classification algorithms? CoRR (2018)
Anthony J. Bagnall, Gavin C. Cawley
On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms. CoRR (2017)
Anthony J. Bagnall, Jason Lines, Aaron Bostrom, James Large, Eamonn J. Keogh
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Discov. 31 (3) (2017)
Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Eamonn J. Keogh
Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series. IEEE BigData (2017)
Aaron Bostrom, Anthony J. Bagnall
Binary Shapelet Transform for Multiclass Time Series Classification. Trans. Large Scale Data Knowl. Centered Syst. 32 (2017)
James Large, Jason Lines, Anthony J. Bagnall
The Heterogeneous Ensembles of Standard Classification Algorithms (HESCA): the Whole is Greater than the Sum of its Parts. CoRR (2017)
Aaron Bostrom, Anthony J. Bagnall
A Shapelet Transform for Multivariate Time Series Classification. CoRR (2017)
Anthony J. Bagnall, Aaron Bostrom, James Large, Jason Lines
Simulated Data Experiments for Time Series Classification Part 1: Accuracy Comparison with Default Settings. CoRR (2017)
Anthony J. Bagnall, Aaron Bostrom, James Large, Jason Lines
The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms. Extended Version. CoRR (2016)
Reda Younsi, Anthony J. Bagnall
Ensembles of random sphere cover classifiers. Pattern Recognit. 49 (2016)
Jason Lines, Sarah Taylor, Anthony J. Bagnall
HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles for Time Series Classification. ICDM (2016)
Anthony J. Bagnall, Jason Lines, Jon Hills, Aaron Bostrom
Time-series classification with COTE: The collective of transformation-based ensembles. ICDE (2016)
Jason Lines, Anthony J. Bagnall
Time series classification with ensembles of elastic distance measures. Data Min. Knowl. Discov. 29 (3) (2015)
Aaron Bostrom, Anthony J. Bagnall
Binary Shapelet Transform for Multiclass Time Series Classification. DaWaK (2015)
Awat A. Saeed, Gavin C. Cawley, Anthony J. Bagnall
Benchmarking the semi-supervised naïve Bayes classifier. IJCNN (2015)
Anthony J. Bagnall, Jason Lines, Jon Hills, Aaron Bostrom
Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles. IEEE Trans. Knowl. Data Eng. 27 (9) (2015)
Jason Lines, Anthony J. Bagnall
Ensembles of Elastic Distance Measures for Time Series Classification. SDM (2014)
Anthony J. Bagnall, Reda Younsi
Ensembles of Random Sphere Cover Classifiers. CoRR (2014)
Anthony J. Bagnall, Luke M. Davis
Predictive Modelling of Bone Age through Classification and Regression of Bone Shapes. CoRR (2014)
Anthony J. Bagnall, Jon Hills, Jason Lines
Finding Motif Sets in Time Series. CoRR (2014)
Anthony J. Bagnall, Gareth J. Janacek
A Run Length Transformation for Discriminating Between Auto Regressive Time Series. J. Classif. 31 (2) (2014)
Anthony J. Bagnall, Jason Lines
An Experimental Evaluation of Nearest Neighbour Time Series Classification. CoRR (2014)
Jon Hills, Jason Lines, Edgaras Baranauskas, James Mapp, Anthony J. Bagnall
Classification of time series by shapelet transformation. Data Min. Knowl. Discov. 28 (4) (2014)
James Mapp, Mark Fisher, Anthony J. Bagnall, Jason Lines, Sally Warne, Joe Scutt Phillips
Clupea Harengus: Intraspecies Distinction using Curvature Scale Space and Shapelets - Classification of North-sea and Thames Herring using Boundary Contour of Sagittal Otoliths. ICPRAM (2013)
Jon Hills, Anthony J. Bagnall, Beatriz de la Iglesia, Graeme Richards
BruteSuppression: a size reduction method for Apriori rule sets. J. Intell. Inf. Syst. 40 (3) (2013)
Luke M. Davis, Barry-John Theobald, Jason Lines, Andoni Toms, Anthony J. Bagnall
On the Segmentation and Classification of Hand Radiographs. Int. J. Neural Syst. 22 (5) (2012)
Jon Hills, Luke M. Davis, Anthony J. Bagnall
Interestingness Measures for Fixed Consequent Rules. IDEAL (2012)
Jason Lines, Anthony J. Bagnall
Alternative Quality Measures for Time Series Shapelets. IDEAL (2012)
Jason Lines, Luke M. Davis, Jon Hills, Anthony J. Bagnall
A shapelet transform for time series classification. KDD (2012)
Luke M. Davis, Barry-John Theobald, Anthony J. Bagnall
Automated Bone Age Assessment Using Feature Extraction. IDEAL (2012)
Reda Younsi, Anthony J. Bagnall
An efficient randomised sphere cover classifier. Int. J. Data Min. Model. Manag. 4 (2) (2012)
Anthony J. Bagnall, Luke M. Davis, Jon Hills, Jason Lines
Transformation Based Ensembles for Time Series Classification. SDM (2012)
Jason Lines, Anthony J. Bagnall, Patrick Caiger-Smith, Simon Anderson
Classification of Household Devices by Electricity Usage Profiles. IDEAL (2011)
Luke M. Davis, Barry-John Theobald, Andoni Toms, Anthony J. Bagnall
On the Extraction and Classification of Hand Outlines. IDEAL (2011)
Reda Younsi, Anthony J. Bagnall
A Randomized Sphere Cover Classifier. IDEAL (2010)
Zhanna V. Zatuchna, Anthony J. Bagnall
A learning classifier system for mazes with aliasing clones. Nat. Comput. 8 (1) (2009)
Zhanna V. Zatuchna, Anthony J. Bagnall
Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception. Adapt. Behav. 17 (1) (2009)
Anthony J. Bagnall, Simon Moxon, David J. Studholme, Vincent Moulton
Time Series Data Mining Algorithms for Identifying Short RNA in Arabidopsis thaliana. BIOCOMP (2008)
Larry Bull, Matthew Studley, Anthony J. Bagnall, Ian M. Whittley
Learning Classifier System Ensembles With Rule-Sharing. IEEE Trans. Evol. Comput. 11 (4) (2007)
Iain Toft, Anthony J. Bagnall
Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets. AMEC/TADA (2007)
Anthony J. Bagnall, Gavin C. Cawley, Ian M. Whittley, Larry Bull, Matthew Studley, Mike Pettipher, Firat Tekiner
Super Computer Heterogeneous Classifier Meta-Ensembles. Int. J. Data Warehous. Min. 3 (2) (2007)
Anthony J. Bagnall, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh, Stefano Lonardi, Gareth J. Janacek
A Bit Level Representation for Time Series Data Mining with Shape Based Similarity. Data Min. Knowl. Discov. 13 (1) (2006)
Anthony J. Bagnall, Ian M. Whittley, Gareth J. Janacek, Kate Kemsley, Matthew Studley, Larry Bull
A Comparison of DWT/PAA and DFT for Time Series Classification. DMIN (2006)
Anthony J. Bagnall, Iain Toft
Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions. Auton. Agents Multi Agent Syst. 12 (3) (2006)
Anthony J. Bagnall, Ian M. Whittley, Matthew Studley, Mike Pettipher, Firat Tekiner, Larry Bull
Variance Stabilizing Regression Ensembles for Environmental Models. IJCNN (2006)
Larry Bull, Matthew Studley, Anthony J. Bagnall, Ian M. Whittley
On the use of rule-sharing in learning classifier system ensembles. Congress on Evolutionary Computation (2005)
Gareth J. Janacek, Anthony J. Bagnall, M. Powell
A Likelihood Ratio Distance Measure for the Similarity Between the Fourier Transform of Time Series. PAKDD (2005)

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Publication Activity (10 Years)

Top Topics

Top Venues

Anthony J. Bagnall