Package weka.core

Examples of weka.core.Instances.classAttribute()

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    // get the maximum class value width (nominal)
    int maxClassWidth = miningSchemaI.classAttribute().name().length();
    if (miningSchemaI.classAttribute().isNominal()
        || miningSchemaI.classAttribute().isString()) {
      for (int i = 0; i < miningSchemaI.classAttribute().numValues(); i++) {
        if (miningSchemaI.classAttribute().value(i).length() > maxClassWidth) {
          maxClassWidth = miningSchemaI.classAttribute().value(i).length();
        }
      }
    }
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    // get the maximum class value width (nominal)
    int maxClassWidth = miningSchemaI.classAttribute().name().length();
    if (miningSchemaI.classAttribute().isNominal()
        || miningSchemaI.classAttribute().isString()) {
      for (int i = 0; i < miningSchemaI.classAttribute().numValues(); i++) {
        if (miningSchemaI.classAttribute().value(i).length() > maxClassWidth) {
          maxClassWidth = miningSchemaI.classAttribute().value(i).length();
        }
      }
    }
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    int maxClassWidth = miningSchemaI.classAttribute().name().length();
    if (miningSchemaI.classAttribute().isNominal()
        || miningSchemaI.classAttribute().isString()) {
      for (int i = 0; i < miningSchemaI.classAttribute().numValues(); i++) {
        if (miningSchemaI.classAttribute().value(i).length() > maxClassWidth) {
          maxClassWidth = miningSchemaI.classAttribute().value(i).length();
        }
      }
    }

    // get the maximum parameter name/label width
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        }
      }
    }

    buff.append("Parameter estimates:\n");
    buff.append(PMMLUtils.pad(miningSchemaI.classAttribute().name(), " ",
                              maxClassWidth + maxParamWidth + 2 -
                              miningSchemaI.classAttribute().name().length(), false));
    buff.append(PMMLUtils.pad("Coeff.", " ", maxBetaWidth + 1 - "Coeff.".length(), true));
    buff.append(PMMLUtils.pad("df", " ", maxBetaWidth - "df".length(), true));
    buff.append("\n");
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    }

    buff.append("Parameter estimates:\n");
    buff.append(PMMLUtils.pad(miningSchemaI.classAttribute().name(), " ",
                              maxClassWidth + maxParamWidth + 2 -
                              miningSchemaI.classAttribute().name().length(), false));
    buff.append(PMMLUtils.pad("Coeff.", " ", maxBetaWidth + 1 - "Coeff.".length(), true));
    buff.append(PMMLUtils.pad("df", " ", maxBetaWidth - "df".length(), true));
    buff.append("\n");
    for (int i = 0; i < m_paramMatrix.length; i++) {
      // scan for non-null entry for this class value
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      }
      if (!ok) {
        continue;
      }
      // first the class value (if nominal)
      String cVal = (miningSchemaI.classAttribute().isNominal() ||
          miningSchemaI.classAttribute().isString())
        ? miningSchemaI.classAttribute().value(i)
        : " ";
      buff.append(PMMLUtils.pad(cVal, " ", maxClassWidth - cVal.length(), false));    
      buff.append("\n");
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      if (!ok) {
        continue;
      }
      // first the class value (if nominal)
      String cVal = (miningSchemaI.classAttribute().isNominal() ||
          miningSchemaI.classAttribute().isString())
        ? miningSchemaI.classAttribute().value(i)
        : " ";
      buff.append(PMMLUtils.pad(cVal, " ", maxClassWidth - cVal.length(), false));    
      buff.append("\n");
      for (int j = 0; j < m_parameterList.size(); j++) {
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        continue;
      }
      // first the class value (if nominal)
      String cVal = (miningSchemaI.classAttribute().isNominal() ||
          miningSchemaI.classAttribute().isString())
        ? miningSchemaI.classAttribute().value(i)
        : " ";
      buff.append(PMMLUtils.pad(cVal, " ", maxClassWidth - cVal.length(), false));    
      buff.append("\n");
      for (int j = 0; j < m_parameterList.size(); j++) {
        PCell p = m_paramMatrix[i][j];
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        TargetMetaInfo targetData = m_miningSchema.getTargetMetaData();
        if (m_miningSchema.getFieldsAsInstances().classAttribute().isNumeric()) {
          preds[0] = targetData.getDefaultValue();
        } else {
          Instances miningSchemaI = m_miningSchema.getFieldsAsInstances();
          for (int i = 0; i < miningSchemaI.classAttribute().numValues(); i++) {
            preds[i] = targetData.getPriorProbability(miningSchemaI.classAttribute().value(i));
          }
        }
        return preds;
      }
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        if (m_miningSchema.getFieldsAsInstances().classAttribute().isNumeric()) {
          preds[0] = targetData.getDefaultValue();
        } else {
          Instances miningSchemaI = m_miningSchema.getFieldsAsInstances();
          for (int i = 0; i < miningSchemaI.classAttribute().numValues(); i++) {
            preds[i] = targetData.getPriorProbability(miningSchemaI.classAttribute().value(i));
          }
        }
        return preds;
      }
    } else {
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