kmeans: Quick-TRANSfer stage steps exceeded maximum

I just had the same issue.

See the documentation of kmeans in R via ?kmeans:

The Hartigan-Wong algorithm generally does a better job than either of those, but trying several random starts (‘nstart’> 1) is often recommended. In rare cases, when some of the points (rows of ‘x’) are extremely close, the algorithm may not converge in the “Quick-Transfer” stage, signalling a warning (and returning ‘ifault = 4’). Slight rounding of the data may be advisable in that case.

In these cases, you may need to switch to the Lloyd or MacQueen algorithms.

The nasty thing about R here is that it continues with a warning that may go unnoticed. For my benchmark purposes, I consider this to be a failed run, and thus I use:

if (kms$ifault==4) { stop("Failed in Quick-Transfer"); }

Depending on your use case, you may want to do something like

if (kms$ifault==4) { kms = kmeans(X, kms$centers, algorithm="MacQueen"); }

instead, to continue with a different algorithm.

If you are benchmarking K-means, note that R uses iter.max=10 per default. It may take much more than 10 iterations to converge.

Had the same problem, seems to have something to do with available memory.

Running Garbage Collection before the function worked for me:

gc()

or reference:

Increasing (or decreasing) the memory available to R processes