41 citations · 58 across the 5 of their papers we have counts for
5 papers · 1 filter
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…
Ensembles of Random Sphere Cover Classifiers
Anthony Bagnall, Reda Younsi
We propose and evaluate alternative ensemble schemes for a new instance based learning classifier, the Randomised Sphere Cover (RSC) classifier. RSC fuses instances into spheres, t…
Finding Motif Sets in Time Series
Anthony Bagnall, Jon Hills, Jason Lines
Time-series motifs are representative subsequences that occur frequently in a time series; a motif set is the set of subsequences deemed to be instances of a given motif. We focus…
Predictive Modelling of Bone Age through Classification and Regression of Bone Shapes
Anthony Bagnall, Luke Davis
Bone age assessment is a task performed daily in hospitals worldwide. This involves a clinician estimating the age of a patient from a radiograph of the non-dominant hand. Our appr…
An Experimental Evaluation of Nearest Neighbour Time Series Classification
Anthony Bagnall, Jason Lines
Data mining research into time series classification (TSC) has focussed on alternative distance measures for nearest neighbour classifiers. It is standard practice to use 1-NN with…