476 citations · 2k across the 27 of their papers we have counts for
29 papers
Convolutional and Deep Learning based techniques for Time Series Ordinal Classification
Rafael Ayllón-Gavilán, David Guijo-Rubio, Pedro Antonio Gutiérrez +2
Time Series Classification (TSC) covers the supervised learning problem where input data is provided in the form of series of values observed through repeated measurements over tim…
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…
A Review and Evaluation of Elastic Distance Functions for Time Series Clustering
Chris Holder, Matthew Middlehurst, Anthony Bagnall
Time series clustering is the act of grouping time series data without recourse to a label. Algorithms that cluster time series can be classified into two groups: those that employ…
The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier
Matthew Middlehurst, Anthony Bagnall
There have recently been significant advances in the accuracy of algorithms proposed for time series classification (TSC). However, a commonly asked question by real world practiti…
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…