/* * RapidMiner * * Copyright (C) 2001-2011 by Rapid-I and the contributors * * Complete list of developers available at our web site: * * http://rapid-i.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 { 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"; } }