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How to pass parameters to the W-BayesNet operator?
Contributor II
Hi:
First, congratulations to all of you for creating the Rapid-I forum and specially for such an awesome program.
My problem is the following. I'm trying to use the Weka classes for Bayes Nets in RapidMiner but I have some problems for getting the operator W-BayesNet to work as I need. The problem is that I need to pass parameters to the weka classes but so far I have not been able to find the best way to do it.
For instance, to implement the K2 algorithm, the Q parameter of W-BayesNet is set to weka.classifiers.bayes.net.search.local.K2. But it is not enough because I need to pass some parameters to this Weka class, as for instance, the parameter P (maximum number of parents), S (score), etc. ( In Weka we use : -Q weka.classifiers.bayes.net.search.local.K2 -- -P 3 -S BAYES)
Any suggestions are very very welcome!!!
Thanks in advance,
Gladys
First, congratulations to all of you for creating the Rapid-I forum and specially for such an awesome program.
My problem is the following. I'm trying to use the Weka classes for Bayes Nets in RapidMiner but I have some problems for getting the operator W-BayesNet to work as I need. The problem is that I need to pass parameters to the weka classes but so far I have not been able to find the best way to do it.
For instance, to implement the K2 algorithm, the Q parameter of W-BayesNet is set to weka.classifiers.bayes.net.search.local.K2. But it is not enough because I need to pass some parameters to this Weka class, as for instance, the parameter P (maximum number of parents), S (score), etc. ( In Weka we use : -Q weka.classifiers.bayes.net.search.local.K2 -- -P 3 -S BAYES)
Any suggestions are very very welcome!!!
Thanks in advance,
Gladys
0
Answers
we will have a look into this and write back if we find out how this can be done...
Cheers,
Ingo
Have you find a way to pass the parameters to the W-BayesNet class? The problem is that next week I will teach a graduate intensive course on Bayes Net for Data Mining and I would like that the students could use RapidMiner instead Weka for evaluating several learning algorithms for BNCs.
Thank you for all your support.
Cheers,
Gladys
I have good news: I found the error. It was actually produced by a bug in Weka for the option handling for the BayesNet learner. It only worked correctly when -E option was also set. I fixed the bug in Weka and changed a setting in RapidMiner (which accidentally removed the -E option due to this Weka bug) and now everything works fine for me. I will send a bug report to the guys in Waikato so that they can fix the error for future versions.
For now, you can access the fixed version (including a fixed Weka library) via CVS. Please refer to http://rapid-i.com/content/view/25/48/ for a description how this can be done. Of course this fix will also be part of the next release.
Cheers and thanks for pointing this out,
Ingo