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how to initializing valueseries plugin

dhaniedhanie Member Posts: 5 Contributor II
edited November 2018 in Help
Hi Ingo,

how to initializing valueseries plugin?

from method: RapidMiner.init();

thank you so much...

Answers

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    IngoRMIngoRM Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,751 RM Founder
    Hi,

    you can get more information about the initialization of RapidMiner together with the plugins in the following thread:

    http://rapid-i.com/rapidforum/index.php/topic,26.0.html

    Hope that helps,
    Ingo
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    dhaniedhanie Member Posts: 5 Contributor II
    Hi..

    I have to write a Java-Application where i want to make RapidMiner GUI for Classifying Audio Data, I use rapidminer.jar (version 4.0) and rapidminer-valueseries-4.0.jar. First step i make process for process automatic feature extraction audio.

    but I got the error-message below :

    G Jul 27, 2008 1:32:38 PM: Loading operators from 'C:\Program Files\RapidMiner\RapidMiner-4.0\lib\plugins\rapidminer-valueseries-4.0.jar'.
    Root[0] (Process)
    +- MusicExampleSource[0] (MusicExampleSource)
    +- ValueSeriesGP[0] (ValueSeriesGP)
    +- XValidation[0] (XValidation)
    +- LibSVMLearner[0] (LibSVMLearner)
    +- ModelApplier[0] (ModelApplier)
    +- PerformanceEvaluator[0] (PerformanceEvaluator)
    P Jul 27, 2008 1:32:40 PM: Initialising process setup
    P Jul 27, 2008 1:32:40 PM: [NOTE] No filename given for result file, using stdout for logging results!
    P Jul 27, 2008 1:32:40 PM: Checking properties...
    P Jul 27, 2008 1:32:40 PM: Properties are ok.
    P Jul 27, 2008 1:32:40 PM: Checking process setup...
    P Jul 27, 2008 1:32:40 PM: [Error] ValueSeriesGP: ValueSeriesGP: Operator has 0 children, should be 1
    P Jul 27, 2008 1:32:40 PM: [Error] XValidation: XValidation: Operator has 0 children, should be 2
    P Jul 27, 2008 1:32:40 PM: [Error] Process setup not ok
    P Jul 27, 2008 1:32:40 PM: [Error] There were 2 errors.
    P Jul 27, 2008 1:32:40 PM: [Warning] PerformanceEvaluator: PerformanceEvaluator: Please use the operators BasicPerformance, RegressionPerformance, ClassificationPerformance, or BinominalClassificationPerformance instead.
    P Jul 27, 2008 1:32:40 PM: [Warning] Deprecations: 1 usage of deprecated operators.
    P Jul 27, 2008 1:32:40 PM: Process initialised
    P Jul 27, 2008 1:32:40 PM: [NOTE] Process starts
    P Jul 27, 2008 1:32:40 PM: Process:
      Root[0] (Process)
      +- MusicExampleSource[0] (MusicExampleSource)
      +- ValueSeriesGP[0] (ValueSeriesGP)
      +- XValidation[0] (XValidation)
      +- LibSVMLearner[0] (LibSVMLearner)
      +- ModelApplier[0] (ModelApplier)
      +- PerformanceEvaluator[0] (PerformanceEvaluator)
    Exception in thread "main" java.lang.RuntimeException: Illegal operator index in getOperator() (ValueSeriesGP): 0
            at com.rapidminer.operator.OperatorChain.getOperator(OperatorChain.java:227)
            at com.rapidminer.valueseries.gp.ValueSeriesGP.evaluate(Unknown Source)
            at com.rapidminer.valueseries.gp.ValueSeriesGP.apply(Unknown Source)
            at com.rapidminer.operator.Operator.apply(Operator.java:648)
            at com.rapidminer.operator.OperatorChain.apply(OperatorChain.java:379)
            at com.rapidminer.operator.Operator.apply(Operator.java:648)
            at com.rapidminer.Process.run(Process.java:545)
            at com.rapidminer.Process.run(Process.java:534)
            at com.rapidminer.Process.run(Process.java:524)
            at seriusne.ProcessCreator.main(ProcessCreator.java:221)

    Plugin is succes loading but there is a message error Exception in thread "main" java.lang.RuntimeException: Illegal operator index in getOperator() (ValueSeriesGP): 0,.
    Could anyone plz let me the solution or where i could be going wrong?

    Thanks and Regards.
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    steffensteffen Member Posts: 347 Maven
    Hello dhanie

    Although I do not know much about the value series plugin...
    P Jul 27, 2008 1:32:40 PM: [Error] P Jul 27, 2008 1:32:40 PM: [Error] ValueSeriesGP: ValueSeriesGP: Operator has 0 children, should be 1
    P Jul 27, 2008 1:32:40 PM: [Error] XValidation: XValidation: Operator has 0 children, should be 2
    P Jul 27, 2008 1:32:40 PM: [Error] Process setup not ok
    P Jul 27, 2008 1:32:40 PM: [Error] There were 2 errors.
    I suggest to create a valid setup and try it again. Maybe the description of the ValueSeriesGP-Operator is helpful.

    greetings

    Steffen
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    IngoRMIngoRM Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,751 RM Founder
    Hi,

    Steffen is right. The ValueSeriesGP operator needs an inner operator delivering a performance vector (this information can be checked in the operator info dialog available from the context menu of the ValueSeriesGP operatoror by pressing F1 after selecting it).

    If you use a cross validation, it again has to have specified children. I would recommend to perform the online tutorial available from the help menu in order to get the basic ideas between the process setups and you should also have a loop into the examples delivered together with the value series plugin (available from the SourceForge download page).

    Cheers,
    Ingo
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    dhaniedhanie Member Posts: 5 Contributor II
    Hello..

    Thanks for the answer, actually i tried to make process for Classifying Audio Data. This is the code for the first step is automatic feature extraction. This code will produced operator for the next step feature extraction in xml file, but still error in the error setup, ValueSeriesGP still can't read the children.. Please help me??

    package seriusne;
    import com.rapidminer.tools.OperatorService;
    import com.rapidminer.RapidMiner;
    import com.rapidminer.Process;
    import com.rapidminer.operator.Operator;
    import java.io.IOException;
    import com.rapidminer.operator.validation.XValidation;     
    import com.rapidminer.operator.learner.functions.kernel.LibSVMLearner;
    import com.rapidminer.operator.ModelApplier; 
    import com.rapidminer.operator.OperatorChain;
    import com.rapidminer.operator.OperatorException;
    import com.rapidminer.operator.performance.PerformanceEvaluator;
    import com.rapidminer.music.*;      
    import com.rapidminer.valueseries.*;
    import com.rapidminer.valueseries.features.*;
    import com.rapidminer.valueseries.functions.*;
    import com.rapidminer.valueseries.gp.ValueSeriesGP;    
    import com.rapidminer.valueseries.transformations.*;
    import com.rapidminer.valueseries.transformations.basis.*;
    import com.rapidminer.valueseries.transformations.filter.*;
    import com.rapidminer.valueseries.transformations.markup.*;
    import com.rapidminer.valueseries.visualizer.*;
    import edu.udo.cs.ai.nemoz.audio.id3lib.*;
    import edu.udo.cs.ai.nemoz.audio.mp3lib.*;
    import codecLib.mp3.*;
    import com.sun.media.codec.audio.mp3.*;

    public class ProcessCreator 
    {  
        public static Process createProcess() 
        {  
            try 
            {
    	System.setProperty(RapidMiner.PROPERTY_RAPIDMINER_INIT_PLUGINS_LOCATION,"C:/Program Files/RapidMiner/RapidMiner-4.0/lib/plugins/");
    	RapidMiner.init();
           }
            catch (IOException e) 
            {
                e. printStackTrace();
            }
           Process ProsesMiningAutomatic = new Process();
            try
            {
           ProsesMiningAutomatic.getRootOperator().setParameter("logverbosity","status");	
           OperatorChain InputOperator = (OperatorChain) OperatorService.createOperator("MusicExampleSource");
           InputOperator.setParameter("create_length_feature","false");
           InputOperator.setParameter("number_of_samples","66150");
           InputOperator.setParameter("source_dir","D:/WULAN/Lagu");
           InputOperator.setParameter("first_sample","0");
           InputOperator.setParameter("random_sample","true");
           InputOperator.setParameter("one_single_instance","false");
           ProsesMiningAutomatic.getRootOperator().addOperator(InputOperator);

    		         OperatorChain satu = (OperatorChain) OperatorService.createOperator("ValueSeriesGP");
                                  satu.setParameter("crossover_prob","0.4");
                                  satu.setParameter("elitist_selection","true");
                                  satu.setParameter("generation_prob","0.4");
                                  satu.setParameter("max_branchings","3");
                                  satu.setParameter("max_generations","30");
                                  satu.setParameter("removal_prob","0.1");
                                  satu.setParameter("xml_output","C:/Hasil/seri.xml");

    		         Operator dua = (Operator) OperatorService.createOperator("OperatorChain");
                                 ProsesMiningAutomatic.getRootOperator().addOperator(satu);
    			  
    		            Operator tiga = (Operator) OperatorService.createOperator("XValidation");
                                     tiga.setParameter("leave_one_out","true");
                                     tiga.setParameter("number_of_validations","5");
                                     ProsesMiningAutomatic.getRootOperator().addOperator(dua);

    					Operator lima = (Operator) OperatorService.createOperator("LibSVMLearner");
    					lima.setParameter("class_weights","");

    					Operator enam = (Operator) OperatorService.createOperator("OperatorChain");
    					ProsesMiningAutomatic.getRootOperator().addOperator(tiga);

    					Operator tujuh = (Operator) OperatorService.createOperator("ModelApplier");
    				          tujuh.setParameter("application_parameters","");

    						Operator delapan = (Operator) OperatorService.createOperator("PerformanceEvaluator");
    						delapan.setParameter("accuracy","true");
    						delapan.setParameter("additional_performance_criteria","");
                                                                 delapan.setParameter("class_weights","");
    						delapan.setParameter("classification_error","true");
    						delapan.setParameter("f_measure","true");
    						delapan.setParameter("main_criterion","accuracy");
    						delapan.setParameter("precision","true");
    						delapan.setParameter("recall","true");       
    						ProsesMiningAutomatic.getRootOperator().addOperator(enam);

    				Operator empat = (Operator) OperatorService.createOperator("ExperimentLog");
    				empat.setParameter("log","");
    				empat.setParameter("Generation","operator.vsGP.value.generation");
    				empat.setParameter("BestEver","operator.vsGP.value.best_ever");
    				empat.setParameter("BestInGen","operator.vsGP.value.best");
    				ProsesMiningAutomatic.getRootOperator().addOperator(dua);
    		}
    		catch (Exception e)	
            {
                e. printStackTrace(); 	
            }
            return ProsesMiningAutomatic;

    	}
    	public static void main(String [] argv) 
             {
            com.rapidminer.Process ProsesMiningAutomatic = createProcess();
            System.out.println(ProsesMiningAutomatic.getRootOperator().createProcessTree(0));
            try 
            {

                ProsesMiningAutomatic.run();
            } 

            catch (OperatorException e)	 
            {
                e.printStackTrace(); 
            }
            System.out.println("membuat rantai process mining.....");
        }
    }
    thank you again..
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