/*
* RapidMiner
*
* Copyright (C) 2001-2008 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.igss.utility;
import com.rapidminer.operator.learner.igss.hypothesis.Hypothesis;
/** The instance-averaging utility function Accuracy.
*
* @author Dirk Dach
* @version $Id: Accuracy.java,v 1.3 2008/05/09 19:23:24 ingomierswa Exp $
*/
public class Accuracy extends InstanceAveraging {
/** Constructs a new Accuracy with the given default probability.*/
public Accuracy(double[] priors,int large) {
super(priors,large);
}
/** Calculates the utility for the given number of examples,positive examples and hypothesis*/
public double utility (double totalExampleWeight, double totalPositiveWeight, Hypothesis hypo) {
double fp=hypo.getCoveredWeight()-hypo.getPositiveWeight();
double tn=totalExampleWeight-totalPositiveWeight-fp;
return (hypo.getPositiveWeight()+tn)/totalExampleWeight;
}
/** Calculates the empirical variance. */
public double variance(double totalWeight, double totalPositiveWeight, Hypothesis hypo) {
double fp=hypo.getCoveredWeight()-hypo.getPositiveWeight();
double tn=totalWeight-totalPositiveWeight-fp;
double correctPredictions=hypo.getPositiveWeight()+tn;
double mean=correctPredictions/totalWeight;
double innerTerm=correctPredictions*Math.pow(1.0d-mean,2)+(totalWeight-correctPredictions)*Math.pow(0.0d-mean,2);
return Math.sqrt(innerTerm)/totalWeight;
}
/** Returns an upper bound for the utility of refinements for the given hypothesis. */
public double getUpperBound(double totalWeight, double totalPositiveWeight, Hypothesis hypo, double delta) {
Hypothesis h=hypo.clone();
h.setCoveredWeight(hypo.getPositiveWeight()); // all fp become tn
double util=this.utility(totalWeight,totalPositiveWeight,h);
double conf=this.confidenceIntervall(totalWeight,delta);
return util+conf;
}
}