Examples of ZeroR

weka.classifiers.rules.ZeroR
Class for building and using a 0-R classifier. Predicts the mean (for a numeric class) or the mode (for a nominal class).
Valid options are:
```
 -D If set, classifier is run in debug mode and may output additional info to the console
```
@author Eibe Frank (eibe@cs.waikato.ac.nz) @version $Revision: 5529 $

Examples of weka.classifiers.rules.ZeroR




  protected void resetOptions () {
    m_trainInstances = null;
    m_Evaluation = null;
    m_BaseClassifier = new ZeroR();
    m_folds = 5;
    m_seed = 1;
    m_threshold = 0.01;
  }

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Examples of weka.classifiers.rules.ZeroR

    newData.deleteWithMissingClass();


    double sum = 0;
    double temp_sum = 0;
    // Add the model for the mean first
    m_zeroR = new ZeroR();
    m_zeroR.buildClassifier(newData);
    
    // only class? -> use only ZeroR model
    if (newData.numAttributes() == 1) {
      System.err.println(

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Examples of weka.classifiers.rules.ZeroR

    
    Random random = new Random(m_Seed);


    m_zeroR = null;
    if (data.numAttributes() == 1) {
      m_zeroR = new ZeroR();
      m_zeroR.buildClassifier(data);
      return;
    }


    // Randomize and stratify

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Examples of weka.classifiers.rules.ZeroR

    insts.deleteWithMissingClass();
    
    if (m_Classifier == null) {
      throw new Exception("No base classifier has been set!");
    }
    m_ZeroR = new ZeroR();
    m_ZeroR.buildClassifier(insts);


    m_TwoClassDataset = null;


    int numClassifiers = insts.numClasses();

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Examples of weka.classifiers.rules.ZeroR

    m_NNSearch.setInstances(m_Train);


    // Invalidate any currently cross-validation selected k
    m_kNNValid = false;
    
    m_defaultModel = new ZeroR();
    m_defaultModel.buildClassifier(instances);
  }

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