KNeighborsRegressor.java

/*
 * Copyright (c) 2016 Villu Ruusmann
 *
 * This file is part of JPMML-SkLearn
 *
 * JPMML-SkLearn 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-SkLearn 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-SkLearn.  If not, see <http://www.gnu.org/licenses/>.
 */
package sklearn.neighbors;

import java.util.List;

import org.dmg.pmml.DataType;
import org.dmg.pmml.MiningFunction;
import org.dmg.pmml.nearest_neighbor.NearestNeighborModel;
import org.jpmml.converter.Schema;
import org.jpmml.converter.ValueUtil;
import org.jpmml.sklearn.ClassDictUtil;
import sklearn.Regressor;

public class KNeighborsRegressor extends Regressor implements HasNeighbors, HasTrainingData {

	public KNeighborsRegressor(String module, String name){
		super(module, name);
	}

	@Override
	public int getNumberOfFeatures(){
		int[] shape = getFitXShape();

		return shape[1];
	}

	@Override
	public DataType getDataType(){
		return DataType.FLOAT;
	}

	@Override
	public NearestNeighborModel encodeModel(Schema schema){
		int[] shape = getFitXShape();

		int numberOfInstances = shape[0];
		int numberOfFeatures = shape[1];

		NearestNeighborModel nearestNeighborModel = KNeighborsUtil.encodeNeighbors(this, MiningFunction.REGRESSION, numberOfInstances, numberOfFeatures, schema)
			.setContinuousScoringMethod(NearestNeighborModel.ContinuousScoringMethod.AVERAGE);

		return nearestNeighborModel;
	}

	@Override
	public int getNumberOfNeighbors(){
		return ValueUtil.asInt((Number)get("n_neighbors"));
	}

	@Override
	public String getWeights(){
		return (String)get("weights");
	}

	@Override
	public String getMetric(){
		return (String)get("metric");
	}

	@Override
	public int getP(){
		return ValueUtil.asInt((Number)get("p"));
	}

	@Override
	public List<? extends Number> getY(){
		return (List)ClassDictUtil.getArray(this, "_y");
	}

	@Override
	public List<? extends Number> getFitX(){
		return (List)ClassDictUtil.getArray(this, "_fit_X");
	}

	private int[] getFitXShape(){
		return ClassDictUtil.getShape(this, "_fit_X", 2);
	}
}