Hi,
With a 9000 observations dataset, I have noticed a significant variability
in the silhouette index when I change the default value for samples (5
default value) and sampsize (40+2*clusters number) in CLARA.
Is there somes rules according to the number of cluster and observations to
fix samples and sampsize parameters efficiently, so as to avoid under- and
oversampling with CLARA in one hand and keeping a good time running in other
hand ?
I didn't not find any rules of this type on the web (except avoiding biaised
samples...).
Gratefully yours.
vincent
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