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[Clus-general] About running clus with Eclipse
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From: Nair b. N. Y. <nai...@ya...> - 2014-01-10 16:36:28
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Hi,
I am using Clus library for some experiments. I have evaluated RF-PCT (Random Forst Predective Clustering) but I am not able to interpret the obtained results without your help. I used Music dataset. The setting file (Music.s) and the output file (Music.test.pred.arff) are described below.
Thanks in advance,
Yacine
---------------------------------
Music.s :
[General]
RandomSeed = 1
[Data]
TestSet = Music_Test.arff
File = Music_Train.arff
XVal = 5
[Attributes]
Target = 1-6
[Model]
[Tree]
Heuristic = VarianceReduction
[Ensemble]
Iterations = 10
EnsembleMethod = RForest
VotingType = ProbabilityDistribution
[Output]
WritePredictions = {Test}
-------------------------------------
Music.test.pred.arff
@RELATION 'Music: -C 6-predictions'
@ATTRIBUTE amazed-suprised {1,0}
@ATTRIBUTE happy-pleased {1,0}
@ATTRIBUTE relaxing-clam {1,0}
@ATTRIBUTE quiet-still {1,0}
@ATTRIBUTE sad-lonely {1,0}
@ATTRIBUTE angry-aggresive {1,0}
@ATTRIBUTE Original-p-amazed-suprised {1,0}
@ATTRIBUTE Original-p-happy-pleased {1,0}
@ATTRIBUTE Original-p-relaxing-clam {1,0}
@ATTRIBUTE Original-p-quiet-still {1,0}
@ATTRIBUTE Original-p-sad-lonely {1,0}
@ATTRIBUTE Original-p-angry-aggresive {1,0}
@ATTRIBUTE Original-p-amazed-suprised-1 numeric
@ATTRIBUTE Original-p-amazed-suprised-0 numeric
@ATTRIBUTE Original-p-happy-pleased-1 numeric
@ATTRIBUTE Original-p-happy-pleased-0 numeric
@ATTRIBUTE Original-p-relaxing-clam-1 numeric
@ATTRIBUTE Original-p-relaxing-clam-0 numeric
@ATTRIBUTE Original-p-quiet-still-1 numeric
@ATTRIBUTE Original-p-quiet-still-0 numeric
@ATTRIBUTE Original-p-sad-lonely-1 numeric
@ATTRIBUTE Original-p-sad-lonely-0 numeric
@ATTRIBUTE Original-p-angry-aggresive-1 numeric
@ATTRIBUTE Original-p-angry-aggresive-0 numeric
@ATTRIBUTE Original-models string
@ATTRIBUTE Pruned-p-amazed-suprised {1,0}
@ATTRIBUTE Pruned-p-happy-pleased {1,0}
@ATTRIBUTE Pruned-p-relaxing-clam {1,0}
@ATTRIBUTE Pruned-p-quiet-still {1,0}
@ATTRIBUTE Pruned-p-sad-lonely {1,0}
@ATTRIBUTE Pruned-p-angry-aggresive {1,0}
@ATTRIBUTE Pruned-p-amazed-suprised-1 numeric
@ATTRIBUTE Pruned-p-amazed-suprised-0 numeric
@ATTRIBUTE Pruned-p-happy-pleased-1 numeric
@ATTRIBUTE Pruned-p-happy-pleased-0 numeric
@ATTRIBUTE Pruned-p-relaxing-clam-1 numeric
@ATTRIBUTE Pruned-p-relaxing-clam-0 numeric
@ATTRIBUTE Pruned-p-quiet-still-1 numeric
@ATTRIBUTE Pruned-p-quiet-still-0 numeric
@ATTRIBUTE Pruned-p-sad-lonely-1 numeric
@ATTRIBUTE Pruned-p-sad-lonely-0 numeric
@ATTRIBUTE Pruned-p-angry-aggresive-1 numeric
@ATTRIBUTE Pruned-p-angry-aggresive-0 numeric
@ATTRIBUTE Pruned-models string
@DATA
0,1,1,0,0,0,0,1,1,0,0,0,0.0,2.0,1.0,1.0,2.0,0.0,0.0,2.0,0.0,2.0,0.0,2.0,"135",0,1,1,0,0,0,2.0,26.0,19.0,9.0,25.0,3.0,2.0,26.0,1.0,27.0,1.0,27.0,"22"
1,0,0,0,0,1,0,1,0,0,1,1,0.0,2.0,1.0,1.0,0.0,2.0,0.0,2.0,1.0,1.0,1.0,1.0,"99",1,0,0,0,0,1,60.0,24.0,12.0,72.0,0.0,84.0,0.0,84.0,5.0,79.0,63.0,21.0,"16"
0,1,0,0,0,1,1,0,0,0,0,1,18.0,0.0,0.0,18.0,0.0,18.0,0.0,18.0,0.0,18.0,18.0,0.0,"89",1,0,0,0,0,1,60.0,24.0,12.0,72.0,0.0,84.0,0.0,84.0,5.0,79.0,63.0,21.0,"16"
0,0,1,0,0,0,0,1,1,0,0,0,0.0,13.0,12.0,1.0,12.0,1.0,0.0,13.0,0.0,13.0,0.0,13.0,"33",0,0,1,0,0,0,10.0,82.0,34.0,58.0,74.0,18.0,17.0,75.0,23.0,69.0,10.0,82.0,"5"
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Le Mardi 22 octobre 2013 15h18, Denny Verbeeck <Den...@cs...> a écrit :
Dear Yacine,
Thank you for your interest in Clus! Clus is designed to be run from the command line, without the need to modify the source files. In general, you provide a settings file (e.g. settings.s), and then you can run Clus at the command line with the following command:
java -jar Clus.jar settings.s
In the manual section 4 is dedicated to this settings file, where you will find the options for selecting a dataset, the target attributes, the ensemble method etc. The other sections in the manual provide examples on how to run Clus and additional command line parameters that can be of interest (e.g. you have to specify the -forest option as a command line parameter, and have an [Ensemble] section in the settings file in order to run ensembles).
Kind regards,
Denny Verbeeck
On Oct 17, 2013, at 18:26 , Nair benrekia Noureddine Yacine wrote:
>
>
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>Hi Denny,
>
>
>I am looking to evaluate a Random Forst Predictive Clustering Tree (RF-PCT) and a Bagging of PCT on some multi-label datasets and for that i need your help please.
>
>
>Below, a part of the main class (Clus.java). The vector args includes the required parameters for running an algorithm. It is also possible to fill in the vector right after (in green color) but which are the entries of the vector necessary to be able to run RF-PCT and Bagging of PCT ?
>
>
>
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>Thanks so much,
>
>
>Yacine NAIR BENREKIA
>
>
>
>
>public static void main(String[] args) {
>try {
>args[0] = "";
>args[1] = "";
>args[2] = "";
> ...
>ClusOutput.printHeader();
>Clus clus = new Clus();
>Settings sett = clus.getSettings();
>CMDLineArgs cargs = new CMDLineArgs(clus);
>cargs.process(args);
>if (cargs.hasOption("copying")) {
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