Parameterizing the cost function of dynamic time warping with application to time series classification

HIGHLIGHTS

  • who: Matthieu Herrmann from the Monash University, Clayton Campus, Woodside Building, Exhibition Walk, Clayton, VIC, Australia have published the research work: Parameterizing the cost function of dynamic time warping with application to time series classification, in the Journal: (JOURNAL)
  • what: The authors show that higher values of u03b3 place greater weight on larger pairwise differences while lower values place greater weight on smaller pairwise differences. The authors demonstrate that training u03b3 significantly improves the accuracy of both the DTW nearest neighbor and Proximity Forest classifiers. Low u03b3 emphasizes low amplitude effects and hence identifies S . . .

     

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