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==WEKA== | ==WEKA== | ||
===Getting Started with Weka=== | |||
Introductory material and full manuals can be found [http://www.cs.waikato.ac.nz/ml/weka/index_documentation.html here]. | |||
There are sample data sets that can be found on Hoffman2 at: | |||
<code><pre>/u/home/FMRI/apps/current/data</pre></code> | |||
and most of these are used in the introductory materials. | |||
=== GUI === | === GUI === | ||
To run the WEKA GUI from Hoffman2 | To run the WEKA GUI from Hoffman2 | ||
Line 25: | Line 33: | ||
<code><pre>/u/home/FMRI/apps/weka/current/weka.jar</pre></code> | <code><pre>/u/home/FMRI/apps/weka/current/weka.jar</pre></code> | ||
A sample command would be<br /> | A sample command would be<br /> | ||
<code><pre>$ java -Xmx2g -cp /u/home/FMRI/apps/weka/current/weka.jar weka.classifiers.functions.SMO -o - | <code><pre>$ java -Xmx2g -cp /u/home/FMRI/apps/weka/current/weka.jar weka.classifiers.functions.SMO -o -t awesome_train_file.arff -T awesome_test_file.arff</pre></code> | ||
where | where | ||
;-Xmx2g | ;-Xmx2g | ||
Line 32: | Line 40: | ||
;-o | ;-o | ||
:suppresses the model output | :suppresses the model output | ||
;- | ;-t awesome_train_file.arff | ||
:specifies the training file | :specifies the training file | ||
;- | ;-T awesome_test_file.arff | ||
:is an optional testing file for the model | :is an optional testing file for the model | ||
:if this option is not provided, 10 fold cross validation will be done | :if this option is not provided, 10 fold cross validation will be done using Training data | ||
== Massive Online Analysis (MOA) == | == Massive Online Analysis (MOA) == |
Revision as of 05:48, 10 August 2011
WEKA
Getting Started with Weka
Introductory material and full manuals can be found here.
There are sample data sets that can be found on Hoffman2 at:
/u/home/FMRI/apps/current/data
and most of these are used in the introductory materials.
GUI
To run the WEKA GUI from Hoffman2
- Make sure that you enabled X11 forwarding by including the -Y flag in your SSH command:
$ ssh -Y joebruin@hoffman2.idre.ucla.edu
- Request an interactive node to run on with the following command:
$ qrsh -l i
- Wait for the new node to appear. Your prompt will change from:
[joebruin@login4 ~] $
to something like
[joebruin@n1234 ~] $
- Run the command:
$ java -jar /u/home/FMRI/apps/weka/current/weka.jar
And the current version of WEKA should start up and the GUI will appear.
Command Line
Calling any of the usual WEKA command line tools will work in submitted jobs so long as you properly reference the WEKA jar file at:
/u/home/FMRI/apps/weka/current/weka.jar
A sample command would be
$ java -Xmx2g -cp /u/home/FMRI/apps/weka/current/weka.jar weka.classifiers.functions.SMO -o -t awesome_train_file.arff -T awesome_test_file.arff
where
- -Xmx2g
- calls for 2GB of memory
- -Xmx256m calls for 256MB of memory
- -o
- suppresses the model output
- -t awesome_train_file.arff
- specifies the training file
- -T awesome_test_file.arff
- is an optional testing file for the model
- if this option is not provided, 10 fold cross validation will be done using Training data
Massive Online Analysis (MOA)
GUI
To run the MOA GUI from Hoffman2
- Make sure that you enabled X11 forwarding by including the -Y flag in your SSH command:
$ ssh -Y joebruin@hoffman2.idre.ucla.edu
- Request an interactive node to run on with the following command:
$ qrsh -l i
- Wait for the new node to appear. Your prompt will change from:
[joebruin@login4 ~] $
to something like
[joebruin@n1234 ~] $
- Run the command:
$ moa.sh
And the current version of MOA should start up and the GUI will appear.
Command Line
Calling any of the usual MOA command line tools will work in submitted jobs so long as you properly reference the MOA jar file at:
/u/home/FMRI/apps/weka/current/weka.jar
A sample command would be
$ java -Xmx4g -cp /u/home/FMRI/apps/moa/current/moa.jar -javaagent:sizeofag.jar moa.DoTask "EvaluatePrequential -l HoeffdingTree -i 1000000 -w 10000"
where
- -Xmx4g
- calls for 4GB of memory
- -Xmx256m calls for 256MB of memory
- EvaluatePrequential -l HoeffdingTree -i 1000000 -w 10000
- is the MOA command to execute