The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
- Submitting institution
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The University of East Anglia
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 182620622
- Type
- D - Journal article
- DOI
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10.1007/s10618-016-0483-9
- Title of journal
- Data Mining and Knowledge Discovery
- Article number
- -
- First page
- 606
- Volume
- 31
- Issue
- 3
- ISSN
- 1384-5810
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
-
-
- Citation count
- 217
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This was the first systematic, reproducible evaluation in the field and had the impact of triggering a wave of algorithmic research. Leading researcher in machine learning, Geoff Webb, Monash University, states in an EPSRC reference “Professor Bagnall has been extremely influential in the field and has had significant impact in developing benchmark tasks and open source toolkits”. It was one of the ten most downloaded Springer CS papers in 2018 in the world (ref: Springer email). It lead to a collaboration with the Alan Turing Institute ([EP/T001569/1]) on the sktime toolkit, and the invitation to organise a Dagstuhl seminar (19282).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -