CSVExampleSource.PARAMETER_COLUMN_META_DATA

Neomatrix433 · February 2013

Hi I have a problem with the CSVExampelSource operator. I want to read a CSVDatei and add them to the DecisionTreeLearner.

How can I add my CSVExampelSource operator attributes and label?

This is my testdata:
Play;Outlook;Temperature;Humidity;Wind
yes;sunny;85;85.0;false
yes;overcast;80;90.0;true
no;overcast;83;78.0;false
no;rain;70;96.0;false
yes;rain;68;80.0;true
no;rain;65;70.0;true
yes;overcast;64;65.0;true
no;sunny;72;95.0;false
yes;sunny;69;70.0;false
no;sunny;75;80.0;false
yes;sunny;68;70.0;true
no;overcast;72;90.0;true
yes;overcast;81;75.0;true
no;rain;71;80.0;true

My code to test:


import java.io.File;
import java.util.LinkedList;
import java.util.List;

import com.rapidminer.Process;
import com.rapidminer.RapidMiner;
import com.rapidminer.RapidMiner.ExecutionMode;
import com.rapidminer.example.Attribute;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.table.AttributeFactory;
import com.rapidminer.operator.IOContainer;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.learner.tree.DecisionTreeLearner;
import com.rapidminer.operator.nio.CSVExampleSource;
import com.rapidminer.operator.preprocessing.filter.ChangeAttributeRole;
import com.rapidminer.tools.Ontology;
import com.rapidminer.tools.OperatorService;

import de.tu_berlin.mf.vlcu.utilityclasses.CSVReader;
public class ProcessCreator {
  public static Process createProcess() {
    // invoke init before using the OperatorService
    RapidMiner.setExecutionMode(ExecutionMode.EMBEDDED_WITH_UI);
    RapidMiner.init();

    String dateipath1 = "./HLB_B3_Messung/Data_Controller/messung1/Testdaten.csv";
    File file = new File(dateipath1);
    CSVReader csvreader = new CSVReader(file.getAbsolutePath());
    csvreader.readCSV();
    String[] header = csvreader.getHeader();
    String[][] data = csvreader.getData();
    Process process = null;
    try {
      // create attribute list
      List<Attribute> attributes = new LinkedList<Attribute>();
      for (int a = 0; a < header.length; a++) {
        if (header.equals("Play")) {
          Attribute label = AttributeFactory.createAttribute("label", Ontology.NOMINAL);
          attributes.add(label);
        } else {
          attributes.add(AttributeFactory.createAttribute("att" + a, Ontology.REAL));
        }
      }
      // create process
      process = new Process();
      /* Reading Data */
      CSVExampleSource csvdata = OperatorService.createOperator(CSVExampleSource.class);
      // set parameters
      csvdata.setParameter(CSVExampleSource.PARAMETER_CSV_FILE, file.getAbsolutePath());
      csvdata.setParameter(CSVExampleSource.PARAMETER_FIRST_ROW_AS_NAMES, "true");
      csvdata.setParameter(CSVExampleSource.PARAMETER_COLUMN_SEPARATORS, ";");
      csvdata.setParameter(CSVExampleSource.PARAMETER_TRIM_LINES, "true");

      ChangeAttributeRole changerole = OperatorService.createOperator(ChangeAttributeRole.class);
      changerole.setParameter(ChangeAttributeRole.PARAMETER_NAME, "Play");
      changerole.setParameter(ChangeAttributeRole.PARAMETER_TARGET_ROLE, Attributes.LABEL_NAME);

      DecisionTreeLearner decisionTree = OperatorService.createOperator(DecisionTreeLearner.class);
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_CRITERION, "gain_ratio");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_SIZE_FOR_SPLIT, "4");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_LEAF_SIZE, "2");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MAXIMAL_DEPTH, "20");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_CONFIDENCE, "0.25");

      process.getRootOperator().getSubprocess(0).addOperator(csvdata);
      process.getRootOperator().getSubprocess(0).addOperator(changerole);
      process.getRootOperator().getSubprocess(0).addOperator(decisionTree);

      csvdata.getOutputPorts().getPortByName("output")
          .connectTo(changerole.getInputPorts().getPortByName("example set input"));
      changerole.getOutputPorts().getPortByName("example set output")
          .connectTo(decisionTree.getInputPorts().getPortByName("training set"));
      // add other operators and set parameters
      // [...]
    } catch (Exception e) {
      e.printStackTrace();
    }
    return process;
  }

  public static void main(String[] argv) {
    // create process
    Process process = createProcess();
    // print process setup
    System.out.println(process.getRootOperator().createProcessTree(0));

    try {
      // perform process
      IOContainer test = process.run();
      System.out.println(test.toString());

      // to run the process with input created by your application use
      // process.run(new IOContainer(new IOObject[] { ... your objects ... });
    } catch (OperatorException e) {
      e.printStackTrace();
    }
  }
}

and this is the output:
Process[0] (Process)
subprocess 'Main Process'
+- Read CSV[0] (Read CSV)
+- Set Role[0] (Set Role)
+- Decision Tree[0] (Decision Tree)

IOContainer (0 objects):

How can I put information if nominal, binominal, real and integer to the CSV operator ....
How can I add to CSVExampelSource Metadata? that the Decision Tree is created by Rapidmineroperator over the label play.

I need urgent help, it's about my Bachelor

And prepare the prozess in rapidminer is not a alternative!!

Sorry for my bad english!!

MFG

Marco_Boeck · March 2013

Hi,

your output looks like you forgot to connect the output port of the last operator to the process output sink.
Anyway, on to your questions:

1) you need to set the parameter "data_set_meta_data_information" on your CSV operator to match the following list


<list key="data_set_meta_data_information">
          <parameter key="0" value="Play.true.binominal.attribute"/>
          <parameter key="1" value="Outlook.true.polynominal.attribute"/>
          <parameter key="2" value="Temperature.true.integer.attribute"/>
          <parameter key="3" value="Humidity.true.real.attribute"/>
          <parameter key="4" value="Wind.true.binominal.attribute"/>
</list>

2) Metadata is for process design help. As you are not using the RapidMiner design perspective to design your process you won't need it
3) If you have exactly one label in your data, the DecisionTree will automatically use it

As a general rule, if you need help on how certain parameters are named or how to use them, go to the RapidMiner design perspective, setup the operator in question there and then have a look at the process XML (XML tab next to the process). Name and values of all parameters can be seen there.

Regards,
Marco

Neomatrix433 · March 2013

Thanks for the replay.

I looked in the xml perpective and picked this out:

public class ProcessCreator {
  public static Process createProcess() {
    // invoke init before using the OperatorService
    RapidMiner.setExecutionMode(ExecutionMode.EMBEDDED_WITH_UI);
    RapidMiner.init();

    String dateipath1 = "./HLB_B3_Messung/Data_Controller/messung1/Testdaten.csv";
    File file = new File(dateipath1);
    CSVReader csvreader = new CSVReader(file.getAbsolutePath());
    csvreader.readCSV();
    Process process = null;
    try {
      // create process
      process = new Process();
      /* Reading Data */
      CSVExampleSource csvdata = OperatorService.createOperator(CSVExampleSource.class);
      // set parameters
      csvdata.setParameter(CSVExampleSource.PARAMETER_CSV_FILE, file.getAbsolutePath());
      csvdata.setParameter(CSVExampleSource.PARAMETER_FIRST_ROW_AS_NAMES, "true");
      csvdata.setParameter(CSVExampleSource.PARAMETER_COLUMN_SEPARATORS, ";");
      csvdata.setParameter(CSVExampleSource.PARAMETER_TRIM_LINES, "true");

      csvdata.setParameter(CSVExampleSource.PARAMETER_META_DATA,
          "<parameter key=\"0\" value=\"Play.true.nominal.label\"/>"
              + "<parameter key=\"1\" value=\"Outlook.true.nominal.attribute\"/>"
              + "<parameter key=\"2\" value=\"Temperature.true.integer.attribute\"/>"
              + "<parameter key=\"3\" value=\"Humidity.true.integer.attribute\"/>"
              + "<parameter key=\"4\" value=\"Wind .true.nominal.attribute\"/>");

      DecisionTreeLearner decisionTree = OperatorService.createOperator(DecisionTreeLearner.class);
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_CRITERION, "gain_ratio");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_SIZE_FOR_SPLIT, "4");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_LEAF_SIZE, "2");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MAXIMAL_DEPTH, "20");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_CONFIDENCE, "0.25");

      process.getRootOperator().getSubprocess(0).addOperator(csvdata);
      process.getRootOperator().getSubprocess(0).addOperator(decisionTree);

      csvdata.getOutputPorts().getPortByName("output")
          .connectTo(decisionTree.getInputPorts().getPortByName("training set"));
      decisionTree.getOutputPorts().getPortByName("model")
          .connectTo(process.getRootOperator().getInputPorts().getPortByName("result 1"));
      // add other operators and set parameters
      // [...]
    } catch (Exception e) {
      e.printStackTrace();
    }
    return process;
  }

  public static void main(String[] argv) {
    // create process
    Process process = createProcess();
    // print process setup
    System.out.println(process.getRootOperator().createProcessTree(0));

    try {
      // perform process
      IOContainer test = process.run();
      System.out.println(test.toString());

      // to run the process with input created by your application use
      // process.run(new IOContainer(new IOObject[] { ... your objects ... });
    } catch (OperatorException e) {
      e.printStackTrace();
    }
  }

then run the Code and the output is:

Process[0] (Process)
subprocess 'Main Process'
+- Read CSV[0] (Read CSV)
+- Decision Tree[0] (Decision Tree)
01.03.2013 14:14:33 com.rapidminer.tools.WrapperLoggingHandler log
INFO: No filename given for result file, using stdout for logging results!
01.03.2013 14:14:33 com.rapidminer.Process run
INFO: Process starts
com.rapidminer.operator.UserError: Input example set does not have a label attribute
at com.rapidminer.operator.learner.AbstractLearner.doWork(AbstractLearner.java:139)
at com.rapidminer.operator.Operator.execute(Operator.java:834)
at com.rapidminer.operator.execution.SimpleUnitExecutor.execute(SimpleUnitExecutor.java:51)
at com.rapidminer.operator.ExecutionUnit.execute(ExecutionUnit.java:711)
at com.rapidminer.operator.OperatorChain.doWork(OperatorChain.java:379)
at com.rapidminer.operator.Operator.execute(Operator.java:834)
at com.rapidminer.Process.run(Process.java:925)
at com.rapidminer.Process.run(Process.java:848)
at com.rapidminer.Process.run(Process.java:807)
at com.rapidminer.Process.run(Process.java:802)
at com.rapidminer.Process.run(Process.java:792)
at de.tu_berlin.mf.vlcu.test.ProcessCreator.main(ProcessCreator.java:95)

What is rong? connecting in this line is correct?

      decisionTree.getOutputPorts().getPortByName("model")
          .connectTo(process.getRootOperator().getInputPorts().getPortByName("result 1"));

i guess the line

 csvdata.setParameter(CSVExampleSource.PARAMETER_META_DATA,
          "<parameter key=\"0\" value=\"Play.true.nominal.label\"/>"
              + "<parameter key=\"1\" value=\"Outlook.true.nominal.attribute\"/>"
              + "<parameter key=\"2\" value=\"Temperature.true.integer.attribute\"/>"
              + "<parameter key=\"3\" value=\"Humidity.true.integer.attribute\"/>"
              + "<parameter key=\"4\" value=\"Wind .true.nominal.attribute\"/>");

is not correct.
This can i read in the errormessage: Input example set does not have a label attribute.
Can anyone show me a Codesample to do this correct?

Thanks and regards

Marco_Boeck · March 2013

Hi,

obviously you cannot use the xml snippet I quoted as a parameter, I merely pointed out the names of the key/value pairs for the list parameter. See ParameterTypeList class and its use in the RapidMiner sourcecode for further details. I guess you will need to dig quite a bit through the RapidMiner sourcecode seeing as for some reason you don't want to use the much less tedious and less error-prone approach to design your processes in the GUI instead of coding everything by hand from scratch.

Regards,
Marco

Neomatrix433 · March 2013

I read the source code of rapidminer (svn Vega i know http://svn.code.sf.net/p/rapidminer/code/Unuk RapidMiner_Unuk is current ;D) but it is very difficult to find the place in the code.

aborg · March 2013

Would you prefer github?
Imho the best is a good IDE for navigation, but having relevant messages for commits would be a welcomed change.

PS.: my fork is a bit out of date, not yet imported the changes since 5.3.5.

Neomatrix433 · March 2013

No SVN is ok i use this form my own projekts

and the vision is ok. I use the search funktion of my IDE Eclipse is very helpfull 8) to find the code places in rapidminer.
is the difference between 5.2 and 5.3.5 so great in reference of my problem?

best regards from berlin ;D

Neomatrix433 · March 2013

i search this function in the code of rapidminer but i cant fund this!

pleace give me a hint to find this in the code, i guess it´s the solution part of my problem.

Marco_Boeck · March 2013

Hi,

that is also a parameter of the CSVExampleSource operator, and it is the one I showed you earlier. You will have to create a ParameterTypeList object, fill it with the given key/value pairs and then add that object to the CSVExampleSource instance under the "data_set_meta_data_information" key.

Regards,
Marco

Neomatrix433 · March 2013

Thanks for the help.

I have change the code:

import java.io.File;
import java.util.ArrayList;
import java.util.List;

import com.rapidminer.Process;
import com.rapidminer.RapidMiner;
import com.rapidminer.operator.IOContainer;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.learner.tree.DecisionTreeLearner;
import com.rapidminer.operator.nio.CSVExampleSource;
import com.rapidminer.tools.OperatorService;

import de.tu_berlin.mf.vlcu.utilityclasses.CSVReader;

public class ProcessCreator {
  public static Process createProcess() {
    // invoke init before using the OperatorService
    // RapidMiner.setExecutionMode(ExecutionMode.EMBEDDED_WITH_UI);
    RapidMiner.init();

    String dateipath1 = "./HLB_B3_Messung/Data_Controller/messung1/Testdaten.csv";
    File file = new File(dateipath1);
    CSVReader csvreader = new CSVReader(file.getAbsolutePath());
    csvreader.readCSV();
    Process process = null;
    try {
      // create process
      process = new Process();
      /* Reading Data */
      CSVExampleSource csvdata = OperatorService.createOperator(CSVExampleSource.class);

      List<String[]> parametertyplist = new ArrayList<String[]>();
      parametertyplist.add(new String[] { "0", "Play.true.nominal.label" });
      parametertyplist.add(new String[] { "1", "Outlook.true.nominal.attribute" });
      parametertyplist.add(new String[] { "2", "Temperature.true.integer.attribute" });
      parametertyplist.add(new String[] { "3", "Humidity.true.integer.attribute" });
      parametertyplist.add(new String[] { "4", "Wind .true.nominal.attribute" });
      csvdata.setParameter(CSVExampleSource.PARAMETER_CSV_FILE, file.getAbsolutePath());
      csvdata.setParameter(CSVExampleSource.PARAMETER_FIRST_ROW_AS_NAMES, "true");
      csvdata.setParameter(CSVExampleSource.PARAMETER_COLUMN_SEPARATORS, ";");
      csvdata.setParameter(CSVExampleSource.PARAMETER_TRIM_LINES, "true");
      csvdata.setListParameter(CSVExampleSource.PARAMETER_META_DATA, parametertyplist);

      DecisionTreeLearner decisionTree = OperatorService.createOperator(DecisionTreeLearner.class);
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_CRITERION, "gain_ratio");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_SIZE_FOR_SPLIT, "4");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_LEAF_SIZE, "2");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_MAXIMAL_DEPTH, "20");
      decisionTree.setParameter(DecisionTreeLearner.PARAMETER_CONFIDENCE, "0.25");

      process.getRootOperator().getSubprocess(0).addOperator(csvdata);
      process.getRootOperator().getSubprocess(0).addOperator(decisionTree);

      csvdata.getOutputPorts().getPortByName("output")
          .connectTo(decisionTree.getInputPorts().getPortByName("training set"));
      decisionTree.getOutputPorts().getPortByName("model")
          .connectTo(process.getRootOperator().getInputPorts().getPortByName("result 1"));
      decisionTree.getOutputPorts().getPortByName("exampleSet")
          .connectTo(process.getRootOperator().getInputPorts().getPortByName("result 2"));
      // add other operators and set parameters
      // [...]
    } catch (Exception e) {
      e.printStackTrace();
    }
    return process;
  }

  public static void main(String[] argv) {
    // create process
    Process process = createProcess();
    // print process setup
    System.out.println(process.getRootOperator().createProcessTree(0));

    try {
      // perform process
      IOContainer test = process.run();
      System.out.println(test.toString());

      // to run the process with input created by your application use
      // process.run(new IOContainer(new IOObject[] { ... your objects ... });
    } catch (OperatorException e) {
      e.printStackTrace();
    }
  }
}

and the result is:

Process[0] (Process)
subprocess 'Main Process'
+- Read CSV[0] (Read CSV)
+- Decision Tree[0] (Decision Tree)
01.03.2013 20:27:44 com.rapidminer.tools.WrapperLoggingHandler log
INFO: No filename given for result file, using stdout for logging results!
01.03.2013 20:27:44 com.rapidminer.Process run
INFO: Process starts
01.03.2013 20:27:44 com.rapidminer.Process run
INFO: Process finished successfully after 0 s
IOContainer (0 objects):

The Problem with label and attributes looks solved......
IOContainer (o objects) what is wrong now ::) ??? ??? ??? ???

What is the problem now? I am a nervous wreck!

aborg · March 2013

Hello,

Could this help you to solve this problem?
HTH, gabor

Neomatrix433 · March 2013

Yes but only the problem with the meta data information for the decision tree.

the iocontainer is still clear!!

    /* Reading Data */
    CSVExampleSource csvdata = OperatorService.createOperator(CSVExampleSource.class);

    List<String[]> parametertyplist = new ArrayList<String[]>();
    parametertyplist.add(new String[] { "0", "Play.true.nominal.label" });
    parametertyplist.add(new String[] { "1", "Outlook.true.nominal.attribute" });
    parametertyplist.add(new String[] { "2", "Temperature.true.integer.attribute" });
    parametertyplist.add(new String[] { "3", "Humidity.true.integer.attribute" });
    parametertyplist.add(new String[] { "4", "Wind.true.nominal.attribute" });
    List<String[]> annotationlist = new ArrayList<String[]>();
    annotationlist.add(new String[] { "0", "Name" });
    csvdata.setParameter(CSVExampleSource.PARAMETER_CSV_FILE, file.getAbsolutePath());
    csvdata.setParameter(CSVExampleSource.PARAMETER_FIRST_ROW_AS_NAMES, "false");
    csvdata.setParameter(CSVExampleSource.PARAMETER_COLUMN_SEPARATORS, ";");
    csvdata.setParameter("encoding", "windows-1252");
    csvdata.setListParameter(CSVExampleSource.PARAMETER_META_DATA, parametertyplist);
    csvdata.setListParameter(CSVExampleSource.PARAMETER_ANNOTATIONS, annotationlist);

    DataResultSetFactory factory = new CSVResultSetConfiguration(csvdata);
    DataResultSetTranslationConfiguration config = new DataResultSetTranslationConfiguration(csvdata);
    // Configure data resultset translation configuration ...
    DataResultSet dataresultset = factory.makeDataResultSet(csvdata);

    DataResultSetTranslator translator = new DataResultSetTranslator(csvdata);
    try {
      ExampleSet cachedExampleSet = translator.read(dataresultset, config, false, null);
      System.out.println(cachedExampleSet.toResultString());
      return new IOContainer(new IOObject[] { cachedExampleSet });
    } finally {
      translator.close();
    }

this is the output of cachedExampleSet :

SimpleExampleSet:
14 examples,
4 regular attributes,
special attributes = {
label = #0: Play (nominal/single_value)/values=[yes, no]
}

the right output should be:

IOContainer (2 objects):

Humidity > 92.500: no {yes=0, no=2}
Humidity ≤ 92.500: yes {yes=7, no=5}
(created by Decision Tree)
SimpleExampleSet:
14 examples,
4 regular attributes,
special attributes = {
label = #0: Play (nominal/single_value)/values=[yes, no]
}
(created by Read CSV)

when I use the process in rapidminer create and export and run this in my own code!

aborg · March 2013

Hello,

Sorry, no experience in this regard, but this might help.
Cheers, gabor

Neomatrix433 · March 2013

My solution for this Problem:

Create a simpel prozess in rapidminer:

and export the prozess with rapidminer in file DecisionTreeprozess.rmp

then use the prozess in my own code:

import java.io.File;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;

import com.rapidminer.Process;
import com.rapidminer.RapidMiner;
import com.rapidminer.RapidMiner.ExecutionMode;
import com.rapidminer.operator.IOContainer;
import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.learner.tree.DecisionTreeLearner;
import com.rapidminer.operator.nio.CSVExampleSource;

public class ProcessCreator {

  private static final String CSVDATEI = "./HLB_B3_Messung/Data_Controller/messung1/Testdaten.csv";
  private static final String PROZESSDATEI = "./HLB_B3_Messung/Data_Controller/messung1/DecisionTreeprozess.rmp";

  public static Process createProcess() {
    // invoke init before using the OperatorService
    RapidMiner.setExecutionMode(ExecutionMode.EMBEDDED_WITHOUT_UI);
    RapidMiner.init();

    Process process = null;
    try {
      // create process
      process = new Process(new File(PROZESSDATEI).getAbsoluteFile());
      // get the list of prozess operators
      List<Operator> operatorlist = process.getRootOperator().getSubprocess(0).getOperators();
      Iterator<Operator> iter = operatorlist.iterator();
      // iterating over the list and set parameters
      while (iter.hasNext()) {
        Operator operator = (Operator) iter.next();
        System.out.println(operator.getName());
        if (operator.getName().equals("Read CSV")) { // check Read CSV
                                                     // operator if true set the
                                                     // parameter to the
                                                     // operator
          List<String[]> parametertyplist = new ArrayList<String[]>(); // meta
                                                                       // data
                                                                       // for
                                                                       // table
                                                                       // data
          parametertyplist.add(new String[] { "0", "Play.true.nominal.label" });
          parametertyplist.add(new String[] { "1", "Outlook.true.nominal.attribute" });
          parametertyplist.add(new String[] { "2", "Temperature.true.integer.attribute" });
          parametertyplist.add(new String[] { "3", "Humidity.true.integer.attribute" });
          parametertyplist.add(new String[] { "4", "Wind.true.nominal.attribute" });
          List<String[]> annotationlist = new ArrayList<String[]>(); // set
                                                                     // annotations
                                                                     // for
                                                                     // columns
          annotationlist.add(new String[] { "0", "Name" });
          operator.setParameter(CSVExampleSource.PARAMETER_CSV_FILE, new File(CSVDATEI).getAbsoluteFile().toString());
          operator.setParameter(CSVExampleSource.PARAMETER_FIRST_ROW_AS_NAMES, "false");
          operator.setParameter(CSVExampleSource.PARAMETER_COLUMN_SEPARATORS, ";");
          operator.setParameter("encoding", "windows-1252");
          operator.setListParameter(CSVExampleSource.PARAMETER_META_DATA, parametertyplist);
          operator.setListParameter(CSVExampleSource.PARAMETER_ANNOTATIONS, annotationlist);
        } else if (operator.getName().equals("Decision Tree")) { // check
                                                                 // Decision
                                                                 // Tree
                                                                 // operator if
                                                                 // true set the
                                                                 // parameter to
                                                                 // the operator
          operator.setParameter(DecisionTreeLearner.PARAMETER_CRITERION, "gain_ratio");
          operator.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_SIZE_FOR_SPLIT, "4");
          operator.setParameter(DecisionTreeLearner.PARAMETER_MINIMAL_LEAF_SIZE, "2");
          operator.setParameter(DecisionTreeLearner.PARAMETER_MAXIMAL_DEPTH, "20");
          operator.setParameter(DecisionTreeLearner.PARAMETER_CONFIDENCE, "0.25");
        }
        // so on check other operators and set parameters when you have more
        // operator in prozess
        // [...]
      }
    } catch (Exception e) {
      e.printStackTrace();
    }
    return process;
  }

  public static void main(String[] argv) {
    // create process
    Process process = createProcess();
    // print process setup
    System.out.println(process.getRootOperator().createProcessTree(0));

    try {
      // perform process
      IOContainer ioResult = process.run();
      // print result
      System.out.println(ioResult.toString());

      // to run the process with input created by your application use
      // process.run(new IOContainer(new IOObject[] { ... your objects ... });
    } catch (OperatorException e) {
      e.printStackTrace();
    }
  }
}

Output of this code:

Read CSV
Decision Tree
Process[0] (Process)
subprocess 'Main Process'
+- Read CSV[0] (Read CSV)
+- Decision Tree[0] (Decision Tree)
02.03.2013 14:18:48 com.rapidminer.tools.WrapperLoggingHandler log
INFO: No filename given for result file, using stdout for logging results!
02.03.2013 14:18:48 com.rapidminer.Process run
INFO: Process

\Anwendungsentwicklung\eclipse 64 Bit\workspace\VLCU_Neu\.\HLB_B3_Messung\Data_Controller\messung1\DecisionTreeprozess.rmp starts
02.03.2013 14:18:48 com.rapidminer.Process run
INFO: Process

\Anwendungsentwicklung\eclipse 64 Bit\workspace\VLCU_Neu\.\HLB_B3_Messung\Data_Controller\messung1\DecisionTreeprozess.rmp finished successfully after 0 s
IOContainer (2 objects):

Humidity > 92.500: no {yes=0, no=2}
Humidity ≤ 92.500: yes {yes=7, no=5}
(created by Decision Tree)
SimpleExampleSet:
14 examples,
4 regular attributes,
special attributes = {
label = #0: Play (nominal/single_value)/values=[yes, no]
}
(created by Read CSV)

Thanks to all helper!!!

pleace close this thread.

CSVExampleSource.PARAMETER_COLUMN_META_DATA

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