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JPMML R to PMML converter
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/*
 * Copyright (c) 2018 Villu Ruusmann
 *
 * This file is part of JPMML-R
 *
 * JPMML-R 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-R 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-R.  If not, see .
 */
package org.jpmml.rexp;

import java.util.List;

import org.dmg.pmml.DataType;
import org.dmg.pmml.MiningFunction;
import org.dmg.pmml.Model;
import org.dmg.pmml.mining.MiningModel;
import org.dmg.pmml.mining.Segmentation;
import org.dmg.pmml.tree.TreeModel;
import org.jpmml.converter.CategoricalLabel;
import org.jpmml.converter.ModelUtil;
import org.jpmml.converter.Schema;
import org.jpmml.converter.mining.MiningModelUtil;

public class BoostingConverter extends AdaBagConverter {

	public BoostingConverter(RGenericVector boosting){
		super(boosting);
	}

	@Override
	public Model encodeModel(Schema schema){
		RGenericVector boosting = getObject();

		RGenericVector trees = boosting.getGenericElement("trees");
		RDoubleVector weights = boosting.getDoubleElement("weights");

		CategoricalLabel categoricalLabel = (CategoricalLabel)schema.getLabel();

		List treeModels = encodeTreeModels(trees);

		MiningModel miningModel = new MiningModel(MiningFunction.CLASSIFICATION, ModelUtil.createMiningSchema(categoricalLabel))
			.setSegmentation(MiningModelUtil.createSegmentation(Segmentation.MultipleModelMethod.WEIGHTED_MAJORITY_VOTE, Segmentation.MissingPredictionTreatment.RETURN_MISSING, treeModels, weights.getValues()))
			.setOutput(ModelUtil.createProbabilityOutput(DataType.DOUBLE, categoricalLabel));

		return miningModel;
	}
}