/*
* 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.tools.math;
/**
* Helper class for finding thresholds for cost sensitive learning or
* calculating the AUC performance criterion.
*
* @author Martin Scholz, Ingo Mierswa
* @version $Id: WeightedConfidenceAndLabel.java,v 1.1 2006/04/13 15:52:03
* ingomierswa Exp $
*/
public class WeightedConfidenceAndLabel implements Comparable {
private double confidence, label, prediction;
private double weight = 1.0d;
public WeightedConfidenceAndLabel(double confidence, double label, double prediction) {
this(confidence, label, prediction, 1.0d);
}
public WeightedConfidenceAndLabel(double confidence, double label, double prediction, double weight) {
this.confidence = confidence;
this.label = label;
this.prediction = prediction;
this.weight = weight;
}
public int compareTo(Object obj) {
// We need to sort the examples by *decreasing* confidence:
int compi = (-1) * Double.compare(this.confidence, ((WeightedConfidenceAndLabel) obj).confidence);
if (compi == 0)
return Double.compare(this.label, ((WeightedConfidenceAndLabel) obj).label);
else
return compi;
}
public boolean equals(Object o) {
if (!(o instanceof WeightedConfidenceAndLabel)) {
return false;
} else {
WeightedConfidenceAndLabel l = (WeightedConfidenceAndLabel)o;
return (this.label == l.label) && (this.confidence == l.confidence);
}
}
public int hashCode() {
return Double.valueOf(this.label).hashCode() ^ Double.valueOf(this.confidence).hashCode();
}
public double getLabel() {
return this.label;
}
public double getPrediction() {
return this.prediction;
}
public double getConfidence() {
return this.confidence;
}
public double getWeight() {
return weight;
}
public String toString() {
return "conf: " + confidence + ", label: " + label + ", weight: " + weight;
}
}