476 citations · 2k across the 27 of their papers we have counts for
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A tale of two toolkits, report the second: bake off redux. Chapter 1. dictionary based classifiers
Anthony Bagnall, James Large, Matthew Middlehurst
Time series classification (TSC) is the problem of learning labels from time dependent data. One class of algorithms is derived from a bag of words approach. A window is run along…
A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency
Anthony Bagnall, Franz Király, Markus Löning +2
sktime is an open source, Python based, sklearn compatible toolkit for time series analysis developed by researchers at the University of East Anglia (UEA), University College Lond…
sktime: A Unified Interface for Machine Learning with Time Series
Markus Löning, Anthony Bagnall, Sajaysurya Ganesh +3
We present sktime -- a new scikit-learn compatible Python library with a unified interface for machine learning with time series. Time series data gives rise to various distinct bu…
Scalable Dictionary Classifiers for Time Series Classification
Matthew Middlehurst, William Vickers, Anthony Bagnall
Dictionary based classifiers are a family of algorithms for time series classification (TSC), that focus on capturing the frequency of pattern occurrences in a time series. The ens…