/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2014 by RapidMiner and the contributors
 *
 *  Complete list of developers available at our web site:
 *
 *       http://rapidminer.com
 *
 *  This program 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.
 *
 *  This program 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 this program.  If not, see http://www.gnu.org/licenses/.
 */
package com.rapidminer.operator.learner.subgroups.utility;

import com.rapidminer.operator.learner.subgroups.hypothesis.Hypothesis;
import com.rapidminer.operator.learner.subgroups.hypothesis.Rule;

/**
 * Calculates the squared error of a rule.
 * 
 * @author Tobias Malbrecht
 */
public class Squared extends UtilityFunction {

	/**
	 * 
	 */
	private static final long serialVersionUID = 1L;

	public Squared(double totalWeight, double totalPredictionWeight) {
		super(totalWeight, totalPredictionWeight);
	}
	
	@Override
	public double utility(Rule rule) {
		double g = rule.getCoveredWeight() / totalWeight;
		double p = rule.getPredictionWeight() / rule.getCoveredWeight();
		double p0 = priors[rule.predictsPositive() ? POSITIVE_CLASS : NEGATIVE_CLASS];
		return g * g * (p - p0);
	}

	@Override
	public double optimisticEstimate(Hypothesis hypothesis) {
		double g = hypothesis.getCoveredWeight() / totalWeight;
		return g * g * Math.max(priors[POSITIVE_CLASS], priors[NEGATIVE_CLASS]);
	}
	
	@Override
	public String getName() {
		return "Squared";
	}
	
	@Override
	public String getAbbreviation() {
		return "Squ";
	}
}