I have been trying to understand where the "mean" or centroid of each cluster is located after using the k-means algorithm with DTW for time series data of different length.
If you use k-medoids, it is clear where the representative time serie of each cluster is since it is a real existing time serie in the data. But how about in case of k-means?
Key points:
- time series data of different length
- no euclidean distance, but DTW
- where is the location of centroids estimated by k-means? -> question
Thanks in advance.
question from:https://stackoverflow.com/questions/65641757/k-means-clustering-time-series-data-of-different-length
