7 citations · 8 across the 3 of their papers we have counts for
7 papers · 1 filter
The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification
Matthew Middlehurst, Aiden Rushbrooke, Ali Ismail-Fawaz +6
Time series machine learning (TSML) is a growing research field that spans a wide range of tasks. The popularity of established tasks such as classification, clustering, and extrin…
aeon: a Python toolkit for learning from time series
Matthew Middlehurst, Ali Ismail-Fawaz, Antoine Guillaume +8
aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regress…
Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression
David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio +2
Time Series Extrinsic Regression (TSER) involves using a set of training time series to form a predictive model of a continuous response variable that is not directly related to th…
Bake off redux: a review and experimental evaluation of recent time series classification algorithms
Matthew Middlehurst, Patrick Schäfer, Anthony Bagnall
In 2017, a research paper compared 18 Time Series Classification (TSC) algorithms on 85 datasets from the University of California, Riverside (UCR) archive. This study, commonly re…
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification
Matthew Middlehurst, James Large, Gavin Cawley +1
Using bag of words representations of time series is a popular approach to time series classification. These algorithms involve approximating and discretising windows over a series…
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…