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Time series classification in reservoir- and model-space: A comparison

: Aswolinskiy, Witali; Reinhart, René Felix; Steil, Jochen


Schwenker, F. ; International Association for Pattern Recognition -IAPR-, Technical Committee on Neural Networks and Computational Intelligence:
Artificial neural networks in pattern recognition : 7th IAPR TC3 International Workshop, ANNPR 2016, Ulm, Germany, September 28-30, 2016. Proceedings
Cham: Springer International Publishing, 2016 (Lecture Notes in Computer Science 9896)
ISBN: 978-3-319-46181-6
ISBN: 978-3-319-46182-3
Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR) <7, 2016, Ulm>
Fraunhofer IEM ()

Learning in the space of Echo State Network (ESN) output weights, i.e. model space, has achieved excellent results in time series classification, visualization and modelling. This work presents a systematic comparison of time series classification in the model space and the classical, discriminative approach with ESNs. We evaluate the approaches on 43 univariate and 18 multivariate time series. It turns out that classification in the model space achieves often better classification rates, especially for high-dimensional motion datasets.