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private void myMethod () {SimpleDateFormat s =
String pattern;new SimpleDateFormat(pattern)
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}
@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);