Hi Suneel,
Thanks for your help.
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Original message
From: Suneel Marthi
Date: 12/24/2013 12:34 PM (GMT-08:00)
To: user@mahout.apache.org
Subject: Re: K-means: No input clusters found
kmeans-init-clusters should be in
Logistic regression with L1 regularization is generally at least as good as
SVM. The problem with SVM is that it uses radially symmetric
regularization which doesn't learn sparse solutions very well. L1
regularization is much better for that.
On Tue, Dec 24, 2013 at 10:06 AM, Steven Bourke wro
kmeans-init-clusters should be in a file with a name like 'part-' and not
the way you have it (kmeans-init-clusters).
On Tuesday, December 24, 2013 2:15 PM, Sameer Tilak wrote:
Hi all,
I get the following problem whehn I run k-mens clustering on my real data. Any
ehlp with this would
Hi all,
I get the following problem whehn I run k-mens clustering on my real data. Any
ehlp with this would be great!
Here is data that I read out of the Sequencefile:
022960 value:
022960:{269830:1.0,2042:1.0,145659:1.0,143547:1.0,219265:1.0,321251:1.0,202350:1.0,258610:1.0,239068:1.0,2591
Just test out libsvm against log regression on a sample of your data to get an
understanding of upside downside for your particular problem
Sent from my iPhone
> On 24 Dec 2013, at 15:55, Tharindu Rusira wrote:
>
> Thanks all for the words of wisdom :) ,
>
> @Ted, I'm coming from a text mini
Thanks all for the words of wisdom :) ,
@Ted, I'm coming from a text mining background. Many text books recommend
SVM because of its impressive performance with vectors having a larger
cardinality which is the usual case when dealing with text documents. Do
you think logistic regression would perf
You can paralize svm using same equations (which has slight difference)
explained in
http://books.google.co.in/books/about/DATA_MINING.html?id=IYc2muhCbmEC&redir_esc=y
But i dont gaurentee about the performance. for some 100 MB data it takes
10 min to train the data.
On Tue, Dec 24, 2013 at 3:30
someone tried to implement SVM in a summer google code but it turns out map
reduced version of svm is too difficult to implement and they dropped the
project.
I bet you can train via libsvm and use just classification part with map
reduce but if I have a choice I prefer logistic regression too
~--
You might try logistic regression with regularization for a very similar
result.
On Mon, Dec 23, 2013 at 11:57 PM, Sebastian Schelter <
ssc.o...@googlemail.com> wrote:
> Hi Tharindu,
>
> There is no SVM implementation in an official release.
>
> --sebastian
>
> On 24.12.2013 08:02, Tharindu Rusi
