Time Series Classification in Reservoir- and Model-Space: A Comparison

  • Witali Aswolinskiy
  • René Felix Reinhart
  • Jochen Steil
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9896)

Abstract

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.

Keywords

Time series classification Echo State Network Model space 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Witali Aswolinskiy
    • 1
  • René Felix Reinhart
    • 2
  • Jochen Steil
    • 1
  1. 1.Research Institute for Cognition and Robotics - CoR-LabBielefeldGermany
  2. 2.Fraunhofer Research Institution for Mechatronic Systems Design IEMPaderbornGermany

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