Hello,
I managed to resolve the problem without modifying the Mahout script.
I inserted my classes into the mahout job jar
(mahout-examples-0.7-cdh4.1.2-job.jar) and everything is ok now.
Thank you very much for your help,
Mihai Josan
-Original Message-
From: Mihai Josan [mailto:mihai.
Well , the --sortVectors for the vectordump utility to evaluate the result
for CVB clistering unfortunately brought me OutofMemory issue...
Here is the case that seem to goes well without --sortVectors option.
$ $MAHOUT_HOME/bin/mahout vectordump -i NHTSA-LDA-sparse -d
NHTSA-vectors01/dictionary.f
I don't think that there are any important differences.
On Tue, Feb 19, 2013 at 3:42 AM, Dan Filimon wrote:
> Are there any differences between these two classes except that
> OnlineSummarizer is used for scalars and OnlineGaussianAccumulator for
> vectors?
>
> They link to the same Wikipedia art
Just to follow up: I now have my real data, which, is much
sparser than the totally-random data … and, unsurprisingly,
it exhibits a good bit more regularity, so it's compressible
to the point that the on-disc SequenceFile is small enough
that there's only a single map job, which, of course, means
Well, even with sparse data, your problem is probably still quite small for
this.
Btw if i have time i will probably put this method into spark rdd and bagel
which should speed things up by removing some inevitable sorting overhead.
In fact, methinks, having mahout sparse vectors and matrices as s
Yes. Recommend the attributes and then do a search for items with those
attributes. You can also combine the final retrieval with a normal
retrieval.
On Tue, Feb 19, 2013 at 9:53 PM, Mohit Anchlia wrote:
> Is it currently possible to use Mahout Recommendation algorithm with
> attributes of a gi
Hi,
I am a beginner in mahout. I am working on k-means MR implementation and
trying to run it on a GPGPU.* I wanted to know if mahout computations are
all double precision or single precision. *
Suggest me any documentation that I need to refer to.
Thanks,
Shruti