ead limit
> > exceeded
> >
> > Is due to to much time CPU time spent in GC, as opposed to not enough
> heap
> > allocation. Decreasing your heap allocation may in fact help as GC is
> more
> > efficient on a smaller heap. You may have to consider GC tuning.
> >
I'm trying to get familiar with the the parallel MapReduce Classification
algorithms offered in Mahout . So far I've run through examples for Naïve
Bayes (classify-20newsgroups.sh) and Random Forest (
https://cwiki.apache.org/MAHOUT/partial-implementation.html). Looking at
the algorithm list (htt
g on every possible label
value.
Thanks,
Adam
On Fri, Dec 28, 2012 at 6:54 PM, Ted Dunning wrote:
> On Fri, Dec 28, 2012 at 5:30 PM, Adam Baron
> wrote:
>
> > I'm trying to get familiar with the the parallel MapReduce Classification
> > algorithms offered in Mah
; > That class is responsible for the partitioning and you can probably
> > just copy that class and replace the map() so that you look at the
> > year from the text somehow.
> >
> > So, while it's not exactly code-free, it's better than writing a new
> >
Frederic,
Adding the functionality to classify new text on a go-forward basis against
an existing Naïve Bayes model would be very helpful functionality to add to
Mahout. I found your blog post informative and I'm sure many other
classification users of Mahout have faced similar challenges to what
Is there a way to set the maximum depth of a Random Forest? Browsing the
code, it looks like the answer is no since the maxDepth() function is
merely an informative property of the Node class (and derived classes).
Just wanted to confirm with more experienced foresters before giving up on
trying
I'm trying to visualize a Random Forest using ForestVisualizer (with the
output redirected to a file) and am getting an OutOfMemoryError:
Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:2882)
at
java.lang.AbstractStringB
I'm attempting to run org.apache.mahout.classifier.df.mapreduce.TestForest
on a CSV with 200,000 rows that have 500,000 features per row.
However, TestForest is running extremely slow, likely because only 1
mapper was assigned to the job. This seems strange because
the org.apache.mahout.classifi
log.info(String.format("min: %,d block: %,d max: %,d split: %,d",
> minSize, blockSize, maxSize, splitSize));
> return splitSize;
> }
>
> It seems like there should be a more straightforward way to do this, but
> it works for me and I've used it on a l
Florian,
Any luck finding an answer over the past 5 months? I'm also dealing with
similar out of memory errors when I run clusterdump. I'm using 50,000
features and tried k=500. The kmeans command ran fine, but then I got the
dreaded OutOfMemory error on with the clusterdump command:
2013-08-0
erdump by limiting the number of terms from
> clusterdump, by specifying -n 20 (outputs the 20 top terms)?
>
>
>
>
> ________
> From: Adam Baron
> To: user@mahout.apache.org
> Sent: Monday, August 5, 2013 8:03 PM
> Subject: Re: How to get hum
. Has the
ClusterDumper code changed in 0.8?
Regards,
Adam
On Tue, Aug 6, 2013 at 9:00 PM, Suneel Marthi wrote:
> Adam,
>
> Pardon my asking again if this has already been answered - Are you running
> against Mahout 0.8?
>
>
>
>
> -----
> Mahout is a library. You can link against any version you like and still
> have a perfectly valid Hadoop program.
>
>
>
>
> On Wed, Aug 7, 2013 at 11:51 AM, Adam Baron
> wrote:
>
> > Suneel,
> >
> > Unfortunately no, we're still on Mahout 0.7.
Tim,
Try using org.apache.mahout.classifier.df.tools.ForestVisualizer:
http://shawnwan.wordpress.com/2012/06/01/mahout-0-7-random-forest-examples/
Regards,
Adam
On Fri, Nov 1, 2013 at 3:33 AM, Tim Peut wrote:
> Hi all,
>
> I'm building a random forest in Mahout 0.8 with
> org.apach
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