List of incorrect() Examples

Examples of incorrect()

weka.classifiers.Evaluation.incorrect()
Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made). (Actually the sum of the weights of these instances) @return the number of incorrectly classified instances

Examples of weka.classifiers.Evaluation.incorrect()

    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());
    
    result[current++] = new Double(eval.correct());
    result[current++] = new Double(eval.incorrect());
    result[current++] = new Double(eval.unclassified());
    result[current++] = new Double(eval.pctCorrect());
    result[current++] = new Double(eval.pctIncorrect());
    result[current++] = new Double(eval.pctUnclassified());
    result[current++] = new Double(eval.totalCost());

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Examples of weka.classifiers.Evaluation.incorrect()

    // number of instances to get absolute numbers
    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());
    result[current++] = new Double(eval.correct());
    result[current++] = new Double(eval.incorrect());
    result[current++] = new Double(eval.unclassified());
    result[current++] = new Double(eval.pctCorrect());
    result[current++] = new Double(eval.pctIncorrect());
    result[current++] = new Double(eval.pctUnclassified());
    result[current++] = new Double(eval.kappa());

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Examples of weka.classifiers.Evaluation.incorrect()

    // number of instances to get absolute numbers
    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());
    result[current++] = new Double(eval.correct());
    result[current++] = new Double(eval.incorrect());
    result[current++] = new Double(eval.unclassified());
    result[current++] = new Double(eval.pctCorrect());
    result[current++] = new Double(eval.pctIncorrect());
    result[current++] = new Double(eval.pctUnclassified());
    result[current++] = new Double(eval.kappa());

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Examples of weka.classifiers.Evaluation.incorrect()

    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());
    
    result[current++] = new Double(eval.correct());
    result[current++] = new Double(eval.incorrect());
    result[current++] = new Double(eval.unclassified());
    result[current++] = new Double(eval.pctCorrect());
    result[current++] = new Double(eval.pctIncorrect());
    result[current++] = new Double(eval.pctUnclassified());
    result[current++] = new Double(eval.totalCost());

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Examples of weka.classifiers.Evaluation.incorrect()

    if (!m_isLeaf) {
      m_isLeaf = true; //temporarily make leaf


      // calculate distribution for evaluation
      eval.evaluateModel(this, m_train);
      m_numIncorrectModel = eval.incorrect();


      m_isLeaf = false;


      for (int i = 0; i < m_Successors.length; i++)
  m_Successors[i].modelErrors();

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Examples of weka.classifiers.Evaluation.incorrect()

      for (int i = 0; i < m_Successors.length; i++)
  m_Successors[i].modelErrors();


    } else {
      eval.evaluateModel(this, m_train);
      m_numIncorrectModel = eval.incorrect();
    }       
  }


  /**
   * Updates the numIncorrectTree field for all nodes. This is needed for

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Examples of weka.classifiers.Evaluation.incorrect()

    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());
    
    result[current++] = new Double(eval.correct());
    result[current++] = new Double(eval.incorrect());
    result[current++] = new Double(eval.unclassified());
    result[current++] = new Double(eval.pctCorrect());
    result[current++] = new Double(eval.pctIncorrect());
    result[current++] = new Double(eval.pctUnclassified());
    result[current++] = new Double(eval.totalCost());

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Examples of weka.classifiers.Evaluation.incorrect()

    // number of instances to get absolute numbers
    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());
    result[current++] = new Double(eval.correct());
    result[current++] = new Double(eval.incorrect());
    result[current++] = new Double(eval.unclassified());
    result[current++] = new Double(eval.pctCorrect());
    result[current++] = new Double(eval.pctIncorrect());
    result[current++] = new Double(eval.pctUnclassified());
    result[current++] = new Double(eval.kappa());

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Examples of weka.classifiers.Evaluation.incorrect()

    if (!m_isLeaf) {
      m_isLeaf = true; //temporarily make leaf


      // calculate distribution for evaluation
      eval.evaluateModel(this, m_train);
      m_numIncorrectModel = eval.incorrect();


      m_isLeaf = false;


      for (int i = 0; i < m_Successors.length; i++)
  m_Successors[i].modelErrors();

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Examples of weka.classifiers.Evaluation.incorrect()

      for (int i = 0; i < m_Successors.length; i++)
  m_Successors[i].modelErrors();


    } else {
      eval.evaluateModel(this, m_train);
      m_numIncorrectModel = eval.incorrect();
    }       
  }


  /**
   * Updates the numIncorrectTree field for all nodes. This is needed for

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