I have a multivariate dataset that changes over time. I have extracted (and normalised) some features and used k-means to generate clusters over the entire span of the dataset.
Now I want to see whether the clusters change significantly over time. So, working backwards, and thus reducing the dataset by x-months, can I see a significant reduction on certain clusters?
This, I think, could fall within the realm of time series clustering. I was hoping to avoid complicating the approach, since the clusters are currently meaningful and the approach is relatively simple.
Could anyone please advise me on how to go about this?
My intuition is to reduce the dataset by x-months and then cluster (using k-means) the data for comparison. However, I may be breaking the rules here, and oversimplifying a complicated problem.