About FURIA in weka

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About FURIA in weka

Betha Nurina Sari
Dear all

I and my friend have read the paper about FURIA, but we are still confused.
After reading the code java of FURIA, so many rows. T_T

We got exercise from my lecture if we use and apply this algorithm, we must know and understand well about furia.

After looking more paper, unfortunately, we are confused again.
May be, you can help us, there are some question :

- Please explain about the step from input dataset until output rule 
- Dataset is partitioned by growing and pruning data, default 3 fold. Is it true that 2 fold for growing data (training data) and 1 fold for pruning data (testing data). Then how the model when use cross validation 10 fold ?  
- What the function Apriori distribution there, is about count frequent itemset, to prepare the candidate rule ?
- Then, how calculate the purity or count and processing the fuzzification phase ?
- Then, how count the CF in final step. How count confidence from the rule?

Your explaination is helpful.

thanks

On Sun, May 21, 2017 at 4:08 AM, <[hidden email]> wrote:
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Today's Topics:

   1. How to execute from the command-line an AutoWEKA result?
      (Gabriel  Del Rio)
   2. Train a model using multiple arff files (Sreynoch.Soung)
   3. Weka-Spark (ENGMohammed kamal)


----------------------------------------------------------------------

Message: 1
Date: Sat, 20 May 2017 14:08:50 -0500 (CDT)
From: "Gabriel  Del Rio" <[hidden email]>
To: [hidden email]
Subject: [Wekalist] How to execute from the command-line an AutoWEKA
        result?
Message-ID:
        <[hidden email]>
Content-Type: text/plain; charset="utf-8"

Hi,


After successfully running auto-weka, I obtained optimum algorithm and hyper parameters for a given dataset. For instance, I got:



best classifier: weka.classifiers.lazy.LWL
arguments: [-A, weka.core.neighboursearch.LinearNNSearch, -W, weka.classifiers.functions.MultilayerPerceptron, --, -L, 0.3899191912662868, -M, 0.4683563849238558, -H, o, -C, -R, -D, -S, 1]
attribute search: null
attribute search arguments: []
attribute evaluation: null
attribute evaluation arguments: []
estimated error: 15.87743732590529


Then, I tried to execute this algorithm with its parameters from the command line as follows:


java -Xmx32g weka.classifiers.lazy.LWL -A "weka.core.neighboursearch.LinearNNSearch" -W "weka.classifiers.functions.MultilayerPerceptron -- -L 0.3899191912662868 -M 0.4683563849238558 -H o -C -R -D -S 1" -t myarffile.arff


(Note, in my computer I have previously set the CLASSPATH so I do not need to call the jar files from weka)


This command renders and error:



Weka exception: weka.classifiers.functions.MultilayerPerceptron -- -L 0.3899191912662868 -M 0.4683563849238558 -H o -C -R -D -S 1


General options:


-h or -help
Output help information.
-synopsis or -info
?. here goes the options to execute weka MultilayerPerceptron


If I change the MultilayerPerceptron parameters to " -- -L 0.3899191912662868 -M 0.4683563849238558 -N 500 -V 0 -E 20 -S 1 -H a ", then I got the following error:



Weka exception: weka.classifiers.functions.MultilayerPerceptron -- -L 0.3899191912662868 -M 0.4683563849238558 -N 500 -V 0 -E 20 -S 1 -H a


General options:


-h or -help
Output help information.
-synopsis or -info
? here goes the options to execute weka MultilayerPerceptron


I have changed the command-line using different parameters that are part of the MultilayerPerceptron (for example, get rind of the "--", etc), and none worked so far, so I'm not sure what I'm doing wrong...Has anyone had tried to execute previously auto-weka best classifier with the specified parameters? Any suggestion on how to succeed in executing the resulting algorithm-parameters?


Any help is appreciated :)


Gabriel





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Message: 2
Date: Sat, 20 May 2017 06:01:06 -0700 (MST)
From: "Sreynoch.Soung" <[hidden email]>
To: [hidden email]
Subject: [Wekalist] Train a model using multiple arff files
Message-ID: <[hidden email]>
Content-Type: text/plain; charset=us-ascii

Hello all,

Is there any ways to train only one model by using multiple arff files (all
files has the same structure) ?
I have multi arff files which are generated. Since, the different arff file
is represented different context that's why I keep it in the separated file.
I'm not sure that incremental learning works in this case since it learns
and updates the model by instance.

Thank you in advanced for your precious response.

Best regards,




--
View this message in context: http://weka.8497.n7.nabble.com/Train-a-model-using-multiple-arff-files-tp40686.html
Sent from the WEKA mailing list archive at Nabble.com.


------------------------------

Message: 3
Date: Sat, 20 May 2017 20:43:17 +0000
From: ENGMohammed kamal <[hidden email]>
To: "[hidden email]" <[hidden email]>
Subject: [Wekalist] Weka-Spark
Message-ID:
        <[hidden email]>

Content-Type: text/plain; charset="iso-8859-1"

Hi all,

i made this spark job on my dataset to learn classifier and test performance i made output to 2 files one for the learned model and the other one for classifier performance , i have some questions?


1-  how to draw ROC curve for the output ?   ( multiclass dataset)

2-  Can i draw ROC for more than one classifier  (if i add another weka classifier spark job for another classifier ???

3- according above job how can i use sampling here (SMOTE or class balancer or subsample) ??
because when i used it with filtered classifier inside weka spark classifier job , i have error ??
please told me exactly where can i use sampling and with what component in knowledge flow interface?
cheers,

M.Kamal


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--
Salam,
Betha Nurina Sari
Fasilkom UNSIKA

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