Here is a sample data set. In this case I asked for 30 and got 28 but in
other cases the discrepancy has been greater like ask for 200 and get 38
but that was for a much larger data set.
Running on my mac laptop in a single node pseudo cluster hadoop
0.20.205, mahout 0.6
command line:
mahout kmeans \
-i b2/bixo-vectors/tfidf-vectors/ \
-c b2/bixo-kmeans-centroids \
-cl \
-o b2/bixo-kmeans-clusters \
-k 30 \
-ow \
-cd 0.01 \
-x 20 \
-dm org.apache.mahout.common.distance.TanimotoDistanceMeasure
Find the data here:
http://cloud.occamsmachete.com/apps/files_sharing/get.php?token=0b2dacddca05c0ee48cbebd05048434425b86740
BTW when I run rowsimilarity asking for 20 similar docs I get a max of
20 but sometimes many less. Shouldn't this always return the requested
number? I'll post this question again to the the attention of the right
person.
On 5/8/12 6:15 AM, Paritosh Ranjan wrote:
I looked at the 0.6 version's code but was not able to find any reason.
If possible, can you share the data you are trying to cluster along
with the execution parameters?
You can also open a Jira for this and provide the info there.
On 07-05-2012 19:45, Pat Ferrel wrote:
0.6
I take it this is not expected behavior? I could be doing something
stupid. I only look in the "final" directory. Looking in the others
with clusterdump shows the same number of clusters and I assumed they
were iterations.
On 5/7/12 1:21 AM, Paritosh Ranjan wrote:
Which version are you using ? 0.6 or the current 0.7-snapshot?
On 07-05-2012 02:19, Pat Ferrel wrote:
What would cause kmeans to not return k clusters? As I tweak
parameters I get different numbers of clusters but it's usually
less than the k I pass in. Since I am not using canopies at present
I would expect k to always be honored but the quality of the
clusters would depend on the convergence amount and number of
iterations allowed. No?
