Susie Zhao | 5 Mar 16:03 2015
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No Classifier output

Hi all,

I am using the Weka 3.6.12 classifier SMO and 10-fold cross-validation on a .csv dataset which has nearly 1,260,000 instances and 22 attributes.

After Weka building model for fold 10, the Status bar shows OK. In the Classifier output window, there is only ===Run information== which is ended by "Time taken to build model: ". 

But nothing afterwards such as === Evaluation on test set ===, === Summary ===.

Has anyone experienced the similar problem before and know how to solve it? Many thanks.

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Rosalvo Neto | 5 Mar 14:59 2015
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Validation testing in the MultiLayerPerceptron (MLP)

Hi there,

I would like to know if the training and validation dataset are disjoint in Weka's MLP.

According to source code MultiLayerPerceptron.java (available in weka-src.jar version 3.7.11), they are overlapping, as can be seen in code below:

// this sets up the validation set.

Instances valSet = null;

// numinval is needed later

int numInVal = (int) (m_valSize / 100.0 * m_instances.numInstances());

if (m_valSize > 0) {

if (numInVal == 0) {

numInVal = 1;

}

valSet = new Instances(m_instances, 0, numInVal);

}

// /////////


m_instances (The training instances) contains valSet.

Please, could you confirm that?


Best regards,

Rosalvo Neto

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Boshra Nabaei | 4 Mar 22:35 2015
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How to retreave the complete CPT of BayesNet?

Hello,

I'm using BayesNet and SimpleEstimator in an unsupervised manner and looking for the joint distribution
of the network.
I know that by using the following:
//*****************************************
BayesNet bn=new BayesNet();
...
SimpleEstimator sbne = new SimpleEstimator();
sbne.estimateCPTs(bn);
...
distributionForInstance(bn,testingsource.instance( i ))
//*****************************************
We will get the Conditional Probability Table(CPT) of the class index for instance i. However I don't know
how to get the (CPT) for every other node (in addition to the class index).
One way would be to recursively change the class index and again call this function but this would be very inefficient.
I'd be very thankful if you help me to retrieve the estimated CPT for every node.

Thanks in advance,
Boshra Nabaei
Masters Student,
Database and Data Mining Laboratory
Simon Fraser University, Vancouver, Ca
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Aylin Caliskan-Islam | 4 Mar 21:59 2015
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Random Forest Possible Memory Leak

Hi,

I encounter a problem with random forests when I have too many classes (>300).  I get the error "array size out of vm limits". It seems like a memory leak. How can this be fixed?

Thanks,
Aylin
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jason roger | 4 Mar 18:02 2015
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classification problem in text mining

Hi all,

I'm working on text classification, and I have the case that one of the instances probably belongs to different cases.

How to deal with this problem in Weka?

Any suggestions would be greatly appreciated.

Thanks.
Jason
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Martin | 4 Mar 17:21 2015
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Re: View selected attributes in Experimenter

The Experimenter is more about *comparing* methods. Hence, you can rely on the WEKA Explorer to explore such aspects.

Regards,
Martin





On 4 March 2015 at 22:41, MenkoD [via WEKA] <[hidden email]> wrote:
Hello,

In the Experimenter I am performing attribute selection with WrapperSubsetEval and NaiveBayes. I want to see the selected attributes for each run, but unfortunately it only shows the number of selected attributes, but not which attributes that are selected.

Is it possible to see the selected attributes in the Experimenter?

Thanks in advance!

Cheers

If you reply to this email, your message will be added to the discussion below:
http://weka.8497.n7.nabble.com/View-selected-attributes-in-Experimenter-tp33884.html
To unsubscribe from WEKA, click here.
NAML


View this message in context: Re: View selected attributes in Experimenter
Sent from the WEKA mailing list archive at Nabble.com.
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Martin | 4 Mar 17:18 2015
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Re: View selected attributes in Experimenter

The Experimenter is more about compressing methods. Hence, you can rely on the WEKA Explorer to explore such aspects.

Regards,
Martin

On 4 March 2015 at 22:41, MenkoD [via WEKA] <[hidden email]> wrote:
Hello,

In the Experimenter I am performing attribute selection with WrapperSubsetEval and NaiveBayes. I want to see the selected attributes for each run, but unfortunately it only shows the number of selected attributes, but not which attributes that are selected.

Is it possible to see the selected attributes in the Experimenter?

Thanks in advance!

Cheers

If you reply to this email, your message will be added to the discussion below:
http://weka.8497.n7.nabble.com/View-selected-attributes-in-Experimenter-tp33884.html
To unsubscribe from WEKA, click here.
NAML


View this message in context: Re: View selected attributes in Experimenter
Sent from the WEKA mailing list archive at Nabble.com.
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Shaun Duerr | 4 Mar 01:40 2015
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please unsubscribe

Please unsubscribe sduerr85 <at> gmail.com
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Michael Hall | 4 Mar 01:21 2015
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Random Forest number of trees

I notice there is a considerable difference in the default number of trees. For 3.6.11 it is 10 but for 3.7.12 it is 100.
Curiosity. Is the 100 sort of experimental? I just upgraded memory and it seems to be working fine. But before I was struggling some with memory trying to increase trees to values like 50.

Michael Hall



AppConverter convert Apple jvm to openjdk apps http://www195.pair.com/mik3hall/index.html#appconverter




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arshdeep kaleka | 3 Mar 10:10 2015
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(no subject)

hi 
actually i get random mails from the wekalist of all the queries subscribers post and i evn tried to unsubscribe by the method you have mentioned  but it showed that i am not subscribed with it so y am i getting all these mails 

i dont want to unsubscribe basically but i evn dont want these unwanted mails to ping over and over. please help so that i dont get these random query mails in my inbox.
Thanks 
regards arsh
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Keith Roy | 2 Mar 15:04 2015
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Incremental learning

Hi WEKA users,

What type of learning does WEKA apply: “Instance- based incremental learning” or “Batch based incremental learning algorithms”?

What are the algorithms that suit such type?


Any assistance would be very much appreciated.


Thanks.
Keith
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Gmane