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20172023
most citedOn the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms

16 citations · 38 across the 5 of their papers we have counts for

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Showing cs.LGShow all

13 papers · 1 filter

cs.LG2023

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…

cs.LG2023

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…

cs.LG2023

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…

cs.LG2021

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…

cs.LG20191 cited

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…

cs.LG20197 cited

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…