/**
* 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.performance;
import java.util.Iterator;
import com.rapidminer.example.Attribute;
import com.rapidminer.example.Example;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.tools.math.Averagable;
/**
* The logistic loss of a classifier, defined as the average over all ln(1 + exp(-y * f(x)))
*
* @author Ingo Mierswa
*/
public class LogisticLoss extends MeasuredPerformance {
private static final long serialVersionUID = -2987795640706342168L;
/** The value of the loss. */
private double loss = Double.NaN;
private double counter = 0.0d;
/** Clone constructor. */
public LogisticLoss() {}
public LogisticLoss(LogisticLoss m) {
super(m);
this.loss = m.loss;
this.counter = m.counter;
}
/** Calculates the margin. */
@Override
public void startCounting(ExampleSet exampleSet, boolean useExampleWeights) throws OperatorException {
super.startCounting(exampleSet, useExampleWeights);
// compute margin
Iterator<Example> reader = exampleSet.iterator();
this.loss = 0.0d;
this.counter = 0.0d;
Attribute labelAttr = exampleSet.getAttributes().getLabel();
Attribute weightAttr = null;
if (useExampleWeights) {
weightAttr = exampleSet.getAttributes().getWeight();
}
while (reader.hasNext()) {
Example example = reader.next();
String trueLabel = example.getNominalValue(labelAttr);
double confidence = example.getConfidence(trueLabel);
double weight = 1.0d;
if (weightAttr != null) {
weight = example.getValue(weightAttr);
}
double currentMargin = weight * Math.log(1.0d + Math.exp(-1 * confidence));
this.loss += currentMargin;
this.counter += weight;
}
}
/** Does nothing. Everything is done in {@link #startCounting(ExampleSet, boolean)}. */
@Override
public void countExample(Example example) {}
@Override
public double getExampleCount() {
return counter;
}
@Override
public double getMikroVariance() {
return Double.NaN;
}
@Override
public double getMikroAverage() {
return this.loss / counter;
}
/**
* Returns 0.
*/
@Override
public double getMaxFitness() {
return 0.0d;
}
/** Returns the fitness. */
@Override
public double getFitness() {
return -1 * getAverage();
}
@Override
public String getName() {
return "logistic_loss";
}
@Override
public String getDescription() {
return "The logistic loss of a classifier, defined as the average of ln(1 + exp(- [confidence of the correct class]))";
}
@Override
public void buildSingleAverage(Averagable performance) {
LogisticLoss other = (LogisticLoss) performance;
this.loss += other.loss;
this.counter += other.counter;
}
/** Returns the super class implementation of toString(). */
@Override
public String toString() {
return super.toString();
}
}