Copied from Cross Validated

I am writing a thesis which compares two approaches to time series classification: Hidden Markov Models and Dynamic Time Warping combined with 1-NN. I'll apply both algorithms to some real dataset, but first it would be nice to show differences in simulation study.

I have already generated samples from 9 HMM instances created with hmmlearn library (all GaussianHMM, with different parameters) and then compared accuracies of classification using HMM vs DTW. Unsuprisingly HMM wins in this case. Now I'm looking for another model to generate data such that this time DTW yields better results. I've tried ARIMA, but results was awful both for HMM and DTW (but still significantly better for HMM). Which model should I use?

  • $\begingroup$ How does the DTW method work? Do you compare the sequence against training examples? Anyway my suggestion would be to try to find real data. $\endgroup$
    – Erwan
    Jul 31, 2022 at 10:57
  • $\begingroup$ The UEA & UCR Time Series Classification Repository has a large number of time series datasets for classification problems, including some simulated datasets. Are any of these suitable for your study? $\endgroup$
    – Lynn
    Aug 1, 2022 at 13:32


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.