Package weka.classifiers

Examples of weka.classifiers.Evaluation.weightedTruePositiveRate()

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    result[current++] = new Double(eval.recall(m_IRclass));
    result[current++] = new Double(eval.fMeasure(m_IRclass));
    result[current++] = new Double(eval.areaUnderROC(m_IRclass));
   
    // Weighted IR stats
    result[current++] = new Double(eval.weightedTruePositiveRate());
    result[current++] = new Double(eval.weightedFalsePositiveRate());
    result[current++] = new Double(eval.weightedTrueNegativeRate());
    result[current++] = new Double(eval.weightedFalseNegativeRate());
    result[current++] = new Double(eval.weightedPrecision());
    result[current++] = new Double(eval.weightedRecall());
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    result[current++] = new Double(eval.recall(m_IRclass));
    result[current++] = new Double(eval.fMeasure(m_IRclass));
    result[current++] = new Double(eval.areaUnderROC(m_IRclass));
   
    // Weighted IR stats
    result[current++] = new Double(eval.weightedTruePositiveRate());
    result[current++] = new Double(eval.weightedFalsePositiveRate());
    result[current++] = new Double(eval.weightedTrueNegativeRate());
    result[current++] = new Double(eval.weightedFalseNegativeRate());
    result[current++] = new Double(eval.weightedPrecision());
    result[current++] = new Double(eval.weightedRecall());
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    result[current++] = new Double(eval.recall(m_IRclass));
    result[current++] = new Double(eval.fMeasure(m_IRclass));
    result[current++] = new Double(eval.areaUnderROC(m_IRclass));
   
    // Weighted IR stats
    result[current++] = new Double(eval.weightedTruePositiveRate());
    result[current++] = new Double(eval.weightedFalsePositiveRate());
    result[current++] = new Double(eval.weightedTrueNegativeRate());
    result[current++] = new Double(eval.weightedFalseNegativeRate());
    result[current++] = new Double(eval.weightedPrecision());
    result[current++] = new Double(eval.weightedRecall());
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