How to use

createPredictedField

method

in

org.jpmml.converter.ModelUtil

  @Override
  public List<OutputField> registerOutputFields(Label label, SparkMLEncoder encoder){
    T model = getTransformer();

    String predictionCol = model.getPredictionCol();

    OutputField predictedField = ModelUtil.createPredictedField(FieldName.create(predictionCol), DataType.STRING, OpType.CATEGORICAL);

    Feature feature = new StringFeature(encoder, predictedField);

    encoder.putOnlyFeature(predictionCol, feature);

    return Collections.singletonList(predictedField);
  }
}

  @Override
  public List<OutputField> registerOutputFields(Label label, SparkMLEncoder encoder){
    T model = getTransformer();

    String predictionCol = model.getPredictionCol();

    OutputField predictedField = ModelUtil.createPredictedField(FieldName.create(predictionCol), label.getDataType(), OpType.CONTINUOUS);

    encoder.putOnlyFeature(predictionCol, new ContinuousFeature(encoder, predictedField));

    return Collections.singletonList(predictedField);
  }
}

OutputField pmmlPredictedField = ModelUtil.createPredictedField(FieldName.create("pmml(" + predictionCol + ")"), categoricalLabel.getDataType(), OpType.CATEGORICAL);

ContinuousLabel continuousLabel = (ContinuousLabel)label;
OutputField predictedField = ModelUtil.createPredictedField(FieldName.create("stack(" + i + ")"), DataType.DOUBLE, OpType.CONTINUOUS)
  .setFinalResult(false);

  predictField = ModelUtil.createPredictedField(name, label.getDataType(), OpType.CONTINUOUS)
    .setFinalResult(false);
} else
  predictField = ModelUtil.createPredictedField(name, label.getDataType(), OpType.CATEGORICAL)
    .setFinalResult(false);
} else

case REGRESSION:
    outputField = ModelUtil.createPredictedField(name, DataType.DOUBLE, OpType.CONTINUOUS)
      .setFinalResult(Boolean.FALSE);