Last modified on 14 Sep 2020.
K-Shape clustering method is a method for clustering time series.
The main ideas of this algorithms are:
- The distance measure is based on the cross-correlation of two time series.
- The clustering process uses iterative approaches.
- It is a raw-based method. It is fundamentally a variant of k-means with some interesting modification.
- Define a distance between 2 time series.
- How to average multiple time series.
- (article) k-Shape: Efficient and Accurate Clustering of Time Series
- Ryan’s blog – K-Shape Clustering Algorithm
•Notes with this notation aren't good enough. They are being updated. If you can see this, you are so smart. ;)