Bagnall, Anthony

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances

Bagnall, A., Lines, J., Bostrom, A., Large, J., & Keogh, E. (2017) · Data Mining and Knowledge Discovery

Time Series Analysis and ForecastingMusic and Audio Processing

Cited by 1,377

The UCR time series archive

Dau, H. A., Bagnall, A., Kamgar, K., Yeh, C.-C. M., Zhu, Y., Gharghabi, S., Ratanamahatana, C. A., & Keogh, E. (2019) · IEEE/CAA Journal of Automatica Sinica

Time Series Analysis and ForecastingData Mining and Machine Learning Applications

Cited by 1,128

Classification of time series by shapelet transformation

Hills, J., Lines, J., Baranauskas, E., Mapp, J., & Bagnall, A. (2014) · Data Mining and Knowledge Discovery

Time Series Analysis and ForecastingImage Retrieval and Classification Techniques

Cited by 538

Time Series Classification with HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles

Lines, J., Taylor, S., & Bagnall, A. (2018) · ACM Transactions on Knowledge Discovery from Data

Time Series Analysis and ForecastingMusic and Audio Processing

Cited by 333

The UEA multivariate time series classification archive, 2018

Bagnall, A., Dau, H. A., Lines, J., Flynn, M., Large, J., Bostrom, A., Southam, P., & Keogh, E. (2018) · arXiv

Time Series Analysis and ForecastingMusic and Audio Processing

Cited by 87