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Java time series machine learning tools in a Weka compatible toolkit
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UEA Time Series Classification

Find more info on our website.

A Weka compatible Java toolbox for time series classification, clustering and transformation. Eventually, we would like to support:


We are looking at getting this on Maven. For now there are two options:

  • download the Jar File
  • download the source file and include in a project in your favourite IDE

you can then construct your own experiment (see or the experimental structure we use (see


We have implemented the following bespoke classifiers for univariate, equal length time series classification

Distance Based

  • DD_DTW
  • DTD_C
  • ElasticEnsemble
  • NN_CID
  • SAX_1NN
  • ProximityForest

Dictionary Based

  • BOSS
  • BOP

Spectral Based

  • RISE

Shaplet Based

  • LearnShapelets
  • ShapeletTransformClassifier
  • FastShapelets

(to do: recover original ShapeletTree)

Interval Based

  • TSF
  • TSBF
  • LPS


  • FlatCote
  • HiveCote

We have implemented the following bespoke classifiers for multivariate, equal length time series classification

  • NN_ED_D
  • NN_ED_I
  • NN_DTW_D
  • NN_DTW_I
  • NN_DTW_A
  • MultivariateShapeletTransformClassifier
  • ConcatenateClassifier


Currently quite limited. Standard approach would be to perform an unsupervised

  • UnsupervisedShapelets


SimpleBatchFilters that take an Instances (the set of time series), transforms them and returns a new Instances object

  • ACF
  • ARMA
  • BagOfPatternsFilter
  • BinaryTransform
  • Clipping
  • Correlation
  • Cosine
  • DerivativeFilter
  • Differences
  • FFT
  • Hilbert
  • MatrixProfile
  • NormalizeAttribute
  • NormalizeCase
  • PAA
  • PACF
  • PowerCepstrum
  • PowerSepstrum
  • RankOrder
  • RunLength
  • SAX
  • Sine
  • SummaryStats
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