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Java library and command-line application for converting Spark ML pipelines to PMML

There is a newer version: 2.5.2

/*
 * Copyright (c) 2016 Villu Ruusmann
 *
 * This file is part of JPMML-SparkML
 *
 * JPMML-SparkML is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Affero General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * JPMML-SparkML is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU Affero General Public License for more details.
 *
 * You should have received a copy of the GNU Affero General Public License
 * along with JPMML-SparkML.  If not, see .
 */
package org.jpmml.sparkml.feature;

import java.util.List;

import org.apache.spark.ml.PipelineModel;
import org.apache.spark.ml.Transformer;
import org.apache.spark.ml.feature.RFormulaModel;
import org.jpmml.converter.Feature;
import org.jpmml.sparkml.ConverterUtil;
import org.jpmml.sparkml.FeatureConverter;
import org.jpmml.sparkml.FeatureMapper;
import org.jpmml.sparkml.TransformerUtil;

public class RFormulaModelConverter extends FeatureConverter {

	public RFormulaModelConverter(RFormulaModel transformer){
		super(transformer);
	}

	@Override
	public List encodeFeatures(FeatureMapper featureMapper){
		RFormulaModel transformer = getTransformer();

		PipelineModel pipelineModel = (PipelineModel)TransformerUtil.getParam(transformer, "pipelineModel");

		Transformer[] stages = pipelineModel.stages();
		for(Transformer stage : stages){
			FeatureConverter featureConverter = ConverterUtil.createFeatureConverter(stage);

			featureMapper.append(featureConverter);
		}

		return null;
	}
}