0
$\begingroup$

I'm working on the same type of data and i want to classify the times series to find clear pattern of use. My data is collected from clients of a telecom company, and we want to detect pattern of the amount of data consumed by clients with their wifi box. So each client have a time series of how much data he consumed each 6minutes (I resampled it to hours). I also applied DTW with KmeansTimeSeries using tslearn:

km = TimeSeriesKMeans(n_clusters = cluster_count, metric="dtw", verbose=1)
labels = km.fit_predict(mySeries)

My question is i want to change the warping window for DTW in python, and i'm pretty sure it's easy think to do, but i just coudn't find a way to do it. I also want to find the best window parameter for my case.

$\endgroup$

1 Answer 1

0
$\begingroup$

Let me help you with the "I also want to find the best window parameter for my case." part of your question. Paper [a] explains how to do it.

[a] Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Abdullah Mueen, Eamonn J. Keogh: Optimizing dynamic time warping's window width for time series data mining applications. Data Min. Knowl. Discov. 32(4): 1074-1120 (2018)

$\endgroup$
1
  • $\begingroup$ Thank you very much $\endgroup$ Jul 5, 2022 at 14:28

Your Answer

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

Not the answer you're looking for? Browse other questions tagged or ask your own question.