Items where Author is "Bagnall, Tony"

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Middlehurst, Matthew, Large, James, Flynn, Michael, Lines, Jason, Bostrom, Aaron and Bagnall, Anthony (2021) HIVE-COTE 2.0: a new meta ensemble for time series classification. Machine Learning, 110. 3211–3243. ISSN 0885-6125

Pasos Ruiz, Alejandro, Flynn, Michael, Large, James, Middlehurst, Matthew and Bagnall, Anthony (2021) The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery, 35. 401–449. ISSN 1384-5810

Middlehurst, Matthew, Large, James, Cawley, Gavin and Bagnall, Anthony (2021) The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. In: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020-09-14 - 2020-09-18.

Bagnall, Tony, Flynn, Michael, Large, James and Middlehurst, Matthew (2020) On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0). In: Lecture Notes in Computer Science. Springer, pp. 3-18. ISBN 978-3-030-65741-3

Guijo-Rubio, David, Gutiérrez, Pedro Antonio, Bagnall, Tony and Hervás-Martínez, César (2020) Ordinal Versus Nominal Time Series Classification. In: Lecture Notes in Computer Science. UNSPECIFIED, pp. 19-29. ISBN 978-3-030-65741-3

Khampuengson, Thakolpat, Bagnall, Tony and Wang, Wenjia (2020) Developing Ensemble Methods for Detecting Anomalies in Water Level Data. In: The 22nd International Conference on Big Data Analytics and Knowledge Discovery. Springer, SVK, pp. 145-151. ISBN 9783030637989

Middlehurst, Matthew, Large, James and Bagnall, Tony (2020) The Canonical Interval Forest {(CIF)} Classifier for Time Series Classification. In: IEEE International Conference on Big Data. IEEE Conference Publications. (In Press)

Guijo-Rubio, David, Gutierrez, Pedro, Bagnall, Tony and Hervás-Martínez, César (2020) Time series ordinal classification via shapelets. In: International Joint Conference on Neural Networks (IJCNN). Proceedings of the International Joint Conference on Neural Networks . UNSPECIFIED, pp. 1-8. ISBN 9781728169262

Gharghabi, Shaghayegh, Imani, Shima, Bagnall, Anthony, Darvishzadeh, Amirali and Keogh, Eamonn (2020) An Ultra-Fast Time Series Distance Measure to allow Data Mining in more Complex Real-World Deployments. Data Mining and Knowledge Discovery, 34 (4). 1104–1135. ISSN 1384-5810

Large, James, Lines, Jason and Bagnall, Anthony (2019) A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates. Data Mining and Knowledge Discovery, 33 (6). pp. 1674-1709. ISSN 1384-5810

Dau, Hoang Anh, Bagnall, Anthony, Kamgar, Kaveh, Yeh, Chin-Chia Michael, Zhu, Yan, Gharghabi, Shaghayegh, Ratanamahatan, Chotirat Ann and Keogh, Eamonn (2019) The UCR Time Series Archive. IEEE/CAA Journal of Automatica Sinica, 6 (6). pp. 1293-1305. ISSN 2329-9266

Large, James, Bagnall, Anthony, Malinowski, Simon and Tavenard, Romain (2019) On Time Series Classification with Dictionary-Based Classifiers. Intelligent Data Analysis, 23 (5). pp. 1073-1089. ISSN 1088-467X

Large, James, Southam, Paul and Bagnall, Anthony (2019) Can Automated Smoothing Significantly Improve Benchmark Time Series Classification Algorithms? In: International Conference on Hybrid Artificial Intelligence Systems. Lecture Notes in Computer Science . Springer, pp. 50-60. ISBN 978-3-030-29858-6

Flynn, Michael and Bagnall, Anthony (2019) Classifying Flies Based on Reconstructed Audio Signals. In: 20th International Conference on Intelligent Data Engineering and Automated Learning. Lecture Notes in Computer Science . Springer, pp. 249-258. ISBN 978-3-030-33616-5

Flynn, Michael, Large, James and Bagnall, Anthony (2019) The Contract Random Interval Spectral Ensemble (c-RISE): The Effect of Contracting a Classifier on Accuracy. In: International Conference on Hybrid Artificial Intelligence Systems. Lecture Notes in Computer Science . Springer, pp. 381-392. ISBN 978-3-030-29858-6

Guijo-Rubio, David, Gutiérrez, Pedro A., Tavenard, Romain and Bagnall, Anthony (2019) A hybrid approach to classification with shapelets. In: 20th International Conference on Intelligent Data Engineering and Automated Learning. Lecture Notes in Computer Science . Springer, pp. 137-144. ISBN 978-3-030-33606-6

Large, James and Bagnall, Anthony (2019) Mixing hetero- and homogeneous models in weighted ensembles. In: 20th International Conference on Intelligent Data Engineering and Automated Learning. Lecture Notes in Computer Science . Springer, pp. 129-136. ISBN 978-3-030-33606-6

Middlehurst, Matthew, Vickers, William and Bagnall, Anthony (2019) Scalable Dictionary Classifiers for Time Series Classification. In: 20th International Conference on Intelligent Data Engineering and Automated Learning. Lecture Notes in Computer Science . Springer, pp. 11-19. ISBN 978-3-030-33606-6

Gharghabi, Shaghayegh, Imani, Shima, Bagnall, Anthony, Darvishzadeh, Amirali and Keogh, Eamonn (2018) Matrix Profile XII: MPDist: A Novel Time Series Distance Measure to allow Data Mining in more Challenging Scenarios. In: IEEE International Conference on Data Mining. UNSPECIFIED, pp. 965-970.

Lines, Jason, Taylor, Sarah and Bagnall, Anthony (2018) Time Series Classification with HIVE-COTE: The Hierarchical Vote Collective of Transformation-based Ensembles. ACM Transactions on Knowledge Discovery from Data, 12 (5). ISSN 1556-4681

Dau, Hoang Anh, Silva, Diego Furtado, Petitjean, Francois, Forestier, Germain, Bagnall, Anthony, Mueen, Abdullah and Keogh, Eamonn (2018) Optimizing Dynamic Time Warping’s Window Width for Time Series Data Mining Applications. Data Mining and Knowledge Discovery, 32 (4). 1074–1120. ISSN 1384-5810

Large, James, Kemsley, E Kate, Wellner, Nikolaus, Goodall, Ian and Bagnall, Anthony (2018) Detecting Forged Alcohol Non-invasively Through Vibrational Spectroscopy and Machine Learning. In: PAKDD 2018: Advances in Knowledge Discovery and Data Mining. Springer, AUS, pp. 298-309. ISBN 978-3-319-93033-6

Dau, Hoang Anh, Silva, Diego Furtado, Petitjean, François, Forestier, Germain, Bagnall, Anthony and Keogh, Eamonn (2017) Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series. In: IEEE International Conference on Big Data. IEEE Conference Publications, USA, pp. 917-922.

Bagnall, Anthony, Lines, Jason, Bostrom, Aaron, Large, James and Keogh, Eamonn (2017) The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery, 31 (3). 606–660. ISSN 1384-5810

Bostrom, Aaron and Bagnall, Anthony (2017) Binary shapelet transform for multiclass time series classification (extended version). In: Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXII. Lecture Notes in Computer Science, 10420 (1). Springer, pp. 24-46. ISBN 978-3-662-55607-8

Lines, Jason, Taylor, Sarah and Bagnall, Anthony (2016) HIVE-COTE: The hierarchical vote collective of transformation-based ensembles for time series classification:IEEE International Conference on Data Mining. In: IEEE ICDM 2016 conference, 2016-12-13 - 2016-12-15.

Bagnall, Anthony, Lines, Jason, Hills, Jon and Bostrom, Aaron (2016) Time-series classification with COTE: The collective of transformation-based ensembles. In: 32nd International Conference on Data Engineering (ICDE), 2016-05-16 - 2016-05-20.

Younsi, Reda and Bagnall, Anthony (2016) Ensembles of random sphere cover classifiers. Pattern Recognition, 49. 213–225.

Bagnall, Anthony, Lines, Jason, Hills, Jon and Bostrom, Aaron (2015) Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles. IEEE Transactions on Knowledge and Data Engineering, 27 (9). pp. 2522-2535. ISSN 1041-4347

Bostrom, Aaron and Bagnall, Anthony (2015) Binary Shapelet Transform for Multiclass Time Series Classification. In: Big Data Analytics and Knowledge Discovery. Lecture Notes in Computer Science, 9263 . Springer, ESP, pp. 257-269. ISBN 978-3-319-22728-3

Saeed, Awat, Cawley, Gavin and Bagnall, Anthony (2015) Benchmarking the Semi-Supervised Naïve Bayes Classifier. In: The International Joint Conference on Neural Networks, 2015-07-12 - 2015-07-17.

Lines, Jason and Bagnall, Anthony (2015) Time series classification with ensembles of elastic distance measures. Data Mining and Knowledge Discovery, 29 (3). pp. 565-592. ISSN 1384-5810

Hills, J., Lines, J, Baranauskas, E., Mapp, J. and Bagnall, A. (2014) Classification of time series by shapelet transformation. Data Mining and Knowledge Discovery, 28 (4). pp. 851-881. ISSN 1384-5810

Bagnall, Anthony and Janacek, Gareth (2014) A Run Length Transformation for Discriminating Between Auto Regressive Time Series. Journal of Classification, 31 (2). pp. 154-178. ISSN 0176-4268

Bagnall, Anthony and Davis, Luke (2014) Predictive Modelling of Bone Age through Classification and Regression of Bone Shapes.

Bagnall, Anthony, Hills, Jon and Lines, Jason (2014) Finding Motif Sets in Time Series.

Bagnall, Anthony and Lines, Jason (2014) An Experimental Evaluation of Nearest Neighbour Time Series Classification.

Lines, Jason and Bagnall, Anthony (2014) Ensembles of Elastic Distance Measures for Time Series Classification. In: Proceedings of the SIAM International Conference on Data Mining, 2012-01-01.

Hills, J, Bagnall, A, De La Iglesia, B and Richards, G (2013) BruteSuppression: a size reduction method for Apriori rule sets. Journal of Intelligent Information Systems, 40 (3). pp. 431-454. ISSN 0925-9902

Mapp, J, Fisher, M, Bagnall, T, Lines, J, Songer, Sally and Scutt Phillips, Joe (2013) Clupea Harengus: Intraspecies Distinction Using Curvature Scale Space and Shapelets. In: Proc. 2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2013), 2013-02-01.

Davis, LM, Theobald, BJ, Lines, J, Toms, A and Bagnall, A (2012) On the segmentation and classification of hand radiographs. International Journal of Neural Systems, 22 (5). pp. 1250020-1250036. ISSN 0129-0657

Bagnall, A, Davis, L, Hills, J and Lines, J (2012) Transformation Based Ensembles for Time Series Classification. In: Proceedings of the SIAM International Conference on Data Mining, 2012-01-01.

Davis, L, Theobald, BJ and Bagnall, A (2012) Automated Bone Age Assessment Using Feature Extraction. Lecture Notes in Computer Sciences, 7435. pp. 43-51. ISSN 0302-9743

Hills, J, Davis, LM and Bagnall, A (2012) Interestingness Measures for Fixed Consequent Rules. Lecture Notes in Computer Sciences, 7435. pp. 68-75. ISSN 0302-9743

Lines, J and Bagnall, A (2012) Alternative Quality Measures for Time Series Shapelets. Lecture Notes in Computer Sciences, 7435. pp. 475-483. ISSN 0302-9743

Lines, J, Davis, L, Hills, J and Bagnall, A (2012) A Shapelet Transform for Time Series Classification. In: Proceedings of the 18th International Conference on Knowledge Discovery in Data and Data Mining, 2012-01-01.

Younsi, R and Bagnall, A (2012) An efficient randomised sphere cover classifier. International Journal of Data Mining, Modelling and Management, 4 (2). p. 156. ISSN 1759-1163

Toms, Andoni P, Farghal, Aser, Kasmai, Bahman, Bagnall, Anthony and Malcolm, Paul N (2011) Physiology of the small bowel:a new approach using MRI and proposal for a new metric of function. Medical Hypotheses, 76 (6). pp. 834-9. ISSN 1532-2777

Davis, L, Theobald, B-J, Toms, A and Bagnall, A (2011) On the Extraction and Classification of Hand Outlines. In: Proceedings onf the 12th International Conference on Intelligent Data Engineering and Automated Learning. Spring, pp. 92-99.

Lines, Jason A., Bagnall, Anthony, Caiger-Smith, Patrick and Anderson, Simon (2011) Classification of Household Devices by Electricity Usage Profiles. Proceedings of the 12th International Conference on Intelligent Data Engineering and Automated Learning. pp. 403-412.

Toms, AP, Farghal, A, Kasmai, B, Bagnall, A and Malcolm, PN (2011) Physiology of the small bowel: a new approach using {MRI} and proposal for a new metric of function. Medical Hypotheses, 76 (6). pp. 834-839. ISSN 1532-2777

Younsi, R and Bagnall, AJ (2010) A Randomized Sphere Cover Classifier. Proceedings of the 11th International Conference on Intelligent Data Engineering and Automated Learning.

Toft, I and Bagnall, A (2009) Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets. Agent-Mediated Electronic Commerce and Trading Agent Design and analysis, 13. pp. 119-134.

Zatuchna, ZV and Bagnall, AJ (2009) A learning classifier system for mazes with aliasing clones. Natural Computing, 8 (1). pp. 57-99. ISSN 1567-7818

Zatuchna, Zhanna V. and Bagnall, Anthony (2009) Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception. Adaptive Behavior, 17 (1). pp. 28-25. ISSN 1059-7123

Bagnall, A, Cawley, G, Whittley, I, Bull, L, Studley, M, Pettipher, M and Tekiner, F (2008) Super Computer Heterogeneous Classifier Meta-Ensembles. In: Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications. IGI Global, pp. 1320-1333. ISBN 978-1599049519

Bagnall, A, Moxon, S and Studholme, D (2008) Time Series Data Mining Algorithms for Identifying Short RNA in Arabidopsis thaliana. In: Proceedings of BIOCOMP 2008, 2008-01-01.

Bagnall, Anthony, Moxon, Simon and Studholme, David (2007) Time Series Data Mining Algorithms for Identifying Short RNA in Arabidopsis thaliana. Working Paper. University of East Anglia.

Bagnall, Anthony J., Cawley, Gavin C., Whittley, Ian M., Bull, Larry, Studley, Matthew, Pettipher, Mike and Tekiner, F. (2007) Super Computer Heterogeneous Classifier Meta-Ensembles. International Journal of Data Warehousing and Mining (IJDWM), 3 (2). pp. 67-82. ISSN 1548-3924

Bull, Larry, Studley, Matthew, Bagnall, Anthony J. and Whittley, Ian M. (2007) Learning Classifier System Ensembles With Rule-Sharing. IEEE Transactions on Evolutionary Computation, 11 (4). pp. 496-502. ISSN 1089-778X

Bagnall, AJ, Whittley, IM, Janacek, GJ, Kemsley, K, Studley, M and Bull, L (2006) A Comparison of DWT/PAA and DFT for Time Series Classification. In: Proceedings of 2006 International Conference on Data Mining, 2006-06-26 - 2006-06-29.

Bagnall, AJ, Whittley, IM, Studley, M, Pettipher, M, Tekiner, F and Bull, L (2006) Variance Stabilizing Regression Ensembles for Environmental Models. In: International Joint Conference on Neural Networks (IJCNN '06), 2006-01-01.

Bagnall, Anthony and Toft, Iain E. (2006) Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions. Journal of Autonomous Agents and Multi-Agent Systems, 12 (3). pp. 259-292. ISSN 1387-2532

Bagnall, Anthony J., Ratanamahatan, Chotirat, Keogh, Eamonn, Lonardi, Stefano and Janacek, Gareth J. (2006) A Bit Level Representation for Time Series Data Mining with Shape Based Similarity. Data Mining and Knowledge Discovery, 13 (1). pp. 11-40. ISSN 1384-5810

Whittley, IM, Bagnall, AJ, Bull, L, Pettipher, M, Studley, M and Tekiner, F (2006) Attribute Selection Methods for Filtered Attribute Subspace based Bagging with Injected Randomness (FASBIR). In: Feature Selection for Data Mining Workshop, Part of the 2006 SIAM Conference on Data Mining, 2006-04-22.

Zatuchna, Z and Bagnall, AJ (2006) A Reinforcement Learning Agent with Associative Perception. In: Symposium on Associative Learning and Reinforcement Learning at Adaptation in Artificial and Biological Systems (AISB'06), 2006-01-01.

Zatuchna, Z and Bagnall, AJ (2006) Modelling of Temperament in an Associative Reinforcement Learning Agent. In: Symposium on Associative Learning and Reinforcement Learning at Adaptation in Artificial and Biological Systems (AISB'06), 2006-01-01.

Bagnall, AJ and Smith, GD (2005) A multiagent model of the UK market in electricity generation. IEEE Transactions on Evolutionary Computation, 9 (5). pp. 522-536. ISSN 1089-778X

Bull, L, Studley, M, Bagnall, AJ and Whittley, IM (2005) On the use of rule-sharing in learning classifier system ensembles. In: Proceedings of the 2005 Congress on Evolutionary Computation, 2005-09-05.

Zatuchna, Z and Bagnall, AJ (2005) AgentP classifier system: self-adjusting vs. gradual approach. In: The 2005 IEEE Congress on Evolutionary Computation, 2005-09-02 - 2005-09-05.

Bagnall, AJ and Janacek, GJ (2005) Clustering time series with clipped data. Machine Learning, 58 (2). pp. 151-178. ISSN 0885-6125

Bagnall, AJ and Zatuchna, Z (2005) On the Classification of Maze Problems. In: Foundations of Learning Classifier Systems. Studies in Fuzziness and Soft Computing, 183 . Springer, pp. 307-316. ISBN 978-3-540-25073-9

Janacek, GJ, Bagnall, AJ and Powell, M (2005) A likelihood ratio distance measure for the similarity between the Fourier transform of time series. In: Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science, 3518 . Springer Berlin / Heidelberg, pp. 205-213.

Ratanamahatan, C, Keogh, E, Bagnall, AJ and Lonardi, S (2005) A Novel Bit Level Time Series Representation with Implication of Similarity Search and Clustering. In: Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science, 3518 . Springer Berlin / Heidelberg, pp. 51-65. ISBN 978-3-540-26076-9

Bagnall, AJ and Janacek, GJ (2004) Clustering time series from ARMA models with clipped data. In: KDD '04 Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, 2004-08-22 - 2004-08-25.

Bagnall, AJ and Toft, IE (2004) Zero Intelligence Plus and Gjerstad-Dickhaut Agents for Sealed Bid Auctions. In: Workshop on Trading Agent Design and Analysis, part of the Third International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2004), 2004-07-20.

Bagnall, AJ and Toft, IE (2004) An Agent Model for First Price and Second Price Private Value Auctions. In: Artificial Evolution. Lecture Notes in Computer Science, 2936 . Springer Berlin / Heidelberg, FRA, pp. 281-292. ISBN 978-3-540-21523-3

Gill, Abdul A., Smith, George D. and Bagnall, Anthony J. (2004) Improving decision tree performance through induction and cluster-based stratified sampling. In: Intelligent Data Engineering and Automated Learning – IDEAL 2004. Lecture Notes in Computer Science, 3177 . Springer, pp. 339-344. ISBN 978-3-540-22881-3

de la Iglesia, B, Philpott, MS, Bagnall, AJ and Rayward-Smith, VJ (2003) Data Mining Rules Using Multi-Objective Evolutionary Algorithms. In: Proceedings of 2003 IEEE Congress on Evolutionary Computation, 2003-12-08 - 2003-12-12.

Bagnall, AJ and Cawley, GC (2003) Learning classifier systems for data mining: a comparison of XCS with other classifiers for the Forest Cover data set. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 2003-07-20 - 2003-07-24.

Bagnall, AJ, Janacek, GJ and Zhang, M (2003) Clustering Time Series from Mixture Polynomial Models with Discretised Data. Working Paper. University of East Anglia.

Bagnall, AJ, Janacek, GJ, de la Iglesia, B and Zhang, M (2003) Clustering Time Series from Mixture Polynomial Models with Discretised Data. In: Proceedings of the second Australasian Data Mining Workshop, 2003-01-01.

Bagnall, AJ, Rayward-Smith, VJ and Whittley, IM (2001) The Next Release Problem. Information and Software Technology, 43 (14). pp. 883-890. ISSN 0950-5849

Bagnall, AJ and Smith, GD (2000) Game playing with autonomous adaptive agents in a simplified economic model of the UK market in electricity generation. In: Proceedings of IEEE-PES / CSEE International conference on power system technology (Powercon 2000), 2000-12-04 - 2000-12-07.

Bagnall, AJ (2000) A Multi-Adaptive Agent Model for Generator Company Bidding in the UK Market in Electricity. In: Genetic and Evolutionary Computation Conference (GECCO-2000), 2000-07-08 - 2000-07-12.

Bagnall, AJ (2000) Modelling the UK market in electricity generation with autonomous adaptive agents. Doctoral thesis, University of East Anglia.

Bagnall, AJ and Smith, GD (2000) An adaptive agent model for generator company bidding in the UK power pool. In: Artificial Evolution. Lecture Notes in Computer Science, 1829 . Springer, pp. 191-203. ISBN 978-3-540-67846-5

This list was generated on Sat Dec 4 10:35:35 2021 GMT.