73 lines
1.7 KiB
Java
73 lines
1.7 KiB
Java
package presenter.evaluation;
|
|
|
|
import model.Line;
|
|
import presenter.algorithms.FastElementSelector;
|
|
|
|
import java.util.ArrayList;
|
|
import java.util.LinkedList;
|
|
|
|
/**
|
|
* Implementierung verschiedener Algorithmen zur Berechnung von Ausgleichsgeraden.
|
|
*
|
|
* @Author: Armin Wolf
|
|
* @Email: a_wolf28@uni-muenster.de
|
|
* @Date: 07.09.2017.
|
|
*/
|
|
public class ScaledErrorBasedMeasure {
|
|
|
|
|
|
private ArrayList<Double> scaledError;
|
|
|
|
public ScaledErrorBasedMeasure(final LinkedList<Line> lines, Double m, Double b) {
|
|
//Liste mit den Fehler zu jedem Punkt
|
|
ArrayList<Double> sampson = new ArrayList<>();
|
|
|
|
|
|
Double denum = 0d;
|
|
for (int i = 2; i < lines.size(); i++) {
|
|
denum += Math.abs(lines.get(i).getM() - lines.get(i - 1).getM());
|
|
}
|
|
denum *= 1 / (lines.size() - 1);
|
|
|
|
for (Line line : lines) {
|
|
Double e = Math.pow(m * line.getM() - line.getB() + b, 2) / (Math.pow(m, 2) + 1);
|
|
sampson.add(e);
|
|
|
|
Double val = e / (denum);
|
|
scaledError.add(val);
|
|
}
|
|
|
|
|
|
}
|
|
|
|
/* Skalierungs Abhängige Approximationsgüten */
|
|
//unterschiedliche Alg.- auf einem Datensatz
|
|
public Double mse() {
|
|
double error = 0;
|
|
for (Double d : scaledError) {
|
|
error += Math.pow(d, 2);
|
|
}
|
|
error /= scaledError.size();
|
|
return error;
|
|
}
|
|
|
|
public Double rmse() {
|
|
return Math.sqrt(mse());
|
|
}
|
|
|
|
public Double mae() {
|
|
double error = 0;
|
|
for (Double d : scaledError) {
|
|
error += Math.abs(d);
|
|
}
|
|
error /= scaledError.size();
|
|
return error;
|
|
}
|
|
|
|
public Double mdae() {
|
|
return FastElementSelector
|
|
.randomizedSelect(scaledError, scaledError.size() * 0.5);
|
|
}
|
|
|
|
}
|