Examples of weka.core.TestInstances.generate()

weka.core.TestInstances.generate()
Generates a new dataset @return the generated data @throws Exception if something goes wrong

    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }
  
  /**
   * Print out a short summary string for the dataset characteristics
   *

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    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }
  
  /**
   * Print out a short summary string for the dataset characteristics
   *

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    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }
  
  /**
   * Print out a short summary string for the dataset characteristics
   *

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    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());
    
    return process(dataset.generate());
  }
  
  /**
   * Print out a short summary string for the dataset characteristics
   *

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    dataset.setNumRelational(attrTypes.relational  ? numAttr : 0);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    
    return process(dataset.generate());
  }


  /**
   * Make a simple set of values. Only one of the num'type' parameters should be larger 0.
   * (just to make parameter similar to the makeTestDataset parameters)

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    dataset.setNumClasses(numClasses);
    dataset.setMultiInstance(multiInstance);
    dataset.setWords(getWords());
    dataset.setWordSeparators(getWordSeparators());


    return process(dataset.generate());
  }


  /**
   * Print out a short summary string for the dataset characteristics
   *

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    dataset.setNumRelational(attrTypes.relational  ? numAttr : 0);
    dataset.setNumClasses(numClasses);
    dataset.setClassType(classType);
    dataset.setClassIndex(classIndex);
    
    return process(dataset.generate());
  }


  /**
   * Make a simple set of values. Only one of the num'type' parameters should be larger 0.
   * (just to make parameter similar to the makeTestDataset parameters)

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    generator.setNumString(0);
    generator.setNumRelational(0);
    generator.setNumInstances(100);
    
    generator.setClassIndex(TestInstances.CLASS_IS_LAST);
    Instances data = generator.generate();
        
    return data;
  }
  
  protected void performTest(boolean nomClass, int numClassesTrain,

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    //     we're using the classifier's capabilities to generate the data.
    test = TestInstances.forCapabilities(
    m_FilteredClassifier.getClassifier().getCapabilities());
    test.setClassIndex(TestInstances.CLASS_IS_LAST);


    result = test.generate();
    
    return result;
  }
  
  /**

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