Hi Lydia,
that is certainly possible, however you need to adapt the algorithm a bit.
The straight-forward approach would be to replicate the input data and
assign IDs for each k-means run.
If you have a data point (1, 2, 3) you could replicate it to three data
points (10, 1, 2, 3), (15, 1, 2, 3),
Hi,
I want to run k-means with different k in parallel.
So each worker should calculate its own k-means. Is that possible?
If I do a map on a list of integers to then apply k-means I get the following
error:
Task not serializable
I am looking forward to your answers!
Lydia
