/**
* Copyright (C) 2001-2017 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 binomial.
*
* @author Tobias Malbrecht
*/
public class Binomial extends UtilityFunction {
/**
*
*/
private static final long serialVersionUID = 1L;
public Binomial(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 Math.sqrt(g) * (p - p0);
}
@Override
public double optimisticEstimate(Hypothesis hypothesis) {
double g = hypothesis.getCoveredWeight() / totalWeight;
return Math.sqrt(g) * Math.max(priors[POSITIVE_CLASS], priors[NEGATIVE_CLASS]);
}
@Override
public String getName() {
return "Binomial";
}
@Override
public String getAbbreviation() {
return "Bin";
}
}